estimating_causal

propensity score analysis篇一：Propensity score analysis (PSA) is a statistical technique used in observational studies to estimate causal effects. It is particularly useful in situations where it is not possible or ethical to conduct randomized controlled trials, and the researcher wants to address potential confounding factors that may affect the outcome of interest.In PSA, the propensity score is defined as the probability of receiving a particular treatment given a set of observed covariates. The main idea behind PSA is to balance the treatment and control groups by matching individuals with similar propensity scores, thus reducing the bias caused by confounding variables.To conduct a propensity score analysis, the researcher follows several steps. First, they specify a model to estimate the propensity scores. This can be done using logistic regression, for example, where the treatment assignment is regressed on the observed covariates. The resulting estimated probabilities represent the propensity scores.Next, the researcher matches or stratifies individuals based on their propensity scores. Matching can be done using various methods, such asnearest neighbor matching or exact matching, to create pairs or groups of individuals with similar propensity scores. Alternatively, stratification involves dividing the sample into strata based on the propensity scores and comparing treatment outcomes within each stratum.After matching or stratifying, the researcher compares the outcomes of the treated and control groups. This can be done using various statistical techniques, such as t-tests or regression models, while accounting for the matched or stratified design. The estimated treatment effect represents the causal effect of the treatment on the outcome of interest.PSA also allows for sensitivity analyses to assess the robustness of the results. This involves examining the effects of potential hidden bias or unobserved confounding variables on the estimated treatment effect. Sensitivity analyses can be conducted by relaxing the assumption of no unobserved confounding or testing the sensitivity of the results to different matching or stratification methods.In conclusion, propensity score analysis is a valuable tool in observational studies to estimate causal effects and address confounding factors. It provides a way to balance treatment and control groups based on observed covariates, reducing bias and improving the validity of causalinference. However, it is important to carefully consider the assumptions and limitations of PSA and conduct sensitivity analyses to ensure the robustness of the results.。

计量经济学因果关系名词解释
在计量经济学中，因果关系是指一个事件或变量对于另一个事件或变量产生直接或间接的影响或作用。

以下是一些与计量经济学因果关系相关的重要名词解释：
1. 因果性（Causality）：指一个事件或变量对另一个事件或变量产生影响的关系。

计量经济学旨在通过研究数据和建立模型，寻找并分析因果关系。

2. 内生性（Endogeneity）：指两个或多个变量之间可能存在相互依赖或相互影响的情况。

内生性是计量经济学中常见的问题，需要采取适当的方法来解决内生性引起的问题。

3. 外生性（Exogeneity）：指一个变量对其他变量没有影响的性质。

外生变量通常被认为是由外部因素决定的，不受模型内其他变量的影响。

4. 差异性（Difference-in-Differences）：是一种计量经济学方法，用于估计政策改变或干预措施对特定群体或地区的因果效应。

通过对比实验组和对照组的差异变化，推断出因果关系。

5. 仪器变量（Instrumental Variables）：是一种用于解决内生性问题的方法。

通过引入一个与内生变量相关但不直接影响被解释变量的仪器变量，可以通过仪器变量估计方法来获得一致的因果效应估计。

6. 因果效应（Causal Effect）：指一个变量或事件对另一个变量或事件产生的直接或间接影响。

计量经济学的目标之一就是通过研
究数据和模型，得出因果效应的估计结果。

2024年深圳市高三年级第一次调研考试英语（答案在最后）2024.2试卷共8页，卷面满分120分，折算成130分计入总分。

考试用时120分钟。

注意事项：1.答题前，先将自己的姓名、准考证号填写在答题卡上，并将准考证号条形码粘贴在答题卡上的指定位置。

用2B铅笔将答题卡上试卷类型A后的方框涂黑。

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写在试题卷、草稿纸和答题卡上的非答题区域均无效。

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4.考试结束后,请将本试题卷和答题卡一并上交。

第二部分阅读(共两节,满分50分)第一节(共15小题;每小题2.5分，满分37.5分)阅读下列短文，从每题所给的A、B、C、D四个选项中选出最佳选项。

AWhistler Travel GuideSnow-capped peaks and powdered steeps;sparkling lakes and rushing waterfalls;challenging hiking routes and inviting restaurants—Whistler's offerings suit every season.Things to doThe entire town displays the ski-chic atmosphere,hosting dozens of ski and snowboardcompetitions and festivals annually.In the warmer months,more outdoor enthusiasts come outto play.Visitors can try hiking or cycling up the mountains.While Whistler is an ideal vacationspot for the active types,other travelers can enjoy the local museums and art galleries filled withinformative exhibits.Plus,there are family-friendly activities and attractions like summerconcerts,along with plenty of shopping options.When to visitThe best times to visit Whistler are from June through August and between December and March. How to get aroundThe best ways to get around Whistler are on foot or by bike.Or,you can take the shuttlebuses from Whistler Village,which transport visitors to Lost Lake Park and the Marketplace.Meanwhile, having a car will allow you the freedom to explore top attractions like WhistlerTrain Wreck and Alexander Falls without having to spend a lot of cash on a cab.What you need to know●Whistler receives feet of snow each year.If you're driving in winter,slow down and make sure to rent or come with a reliable SUV.●Snowslides are likely to occur on Backcountry routes,so only advanced skiers should take to this off-the-map area.●Whistler's wildermess is home to many black and grizzly bears.Keep your distance anddo not feed them.21.What are active travelers recommended to do in Whistler?A.Bike up the mountains.B.Host ski competitions.C.Go shopping at the malls.D.Visit museum exhibitions.22.Which of the following is the most popular among travelers?A.Whistler Village.B.Lost Lake Park.C.The Marketplace.D.Whistler Train Wreck.23.What are travelers prohibited from doing in Whistler?A.Driving a rented SUV.B.Feeding grizzly bears.C.Exploring the wilderness.D.Sking on Backcountry routes.BI used to believe that only words could catch the essence of the human soul.The literary works contained such distinct stories that they shaped the way we saw the world.Words were what composed the questions we sought to uncover and the answers to those questions themselves.Words were everything.That belief changed.In an ordinary math class,my teacher posed a simple question:What's0.99rounded to the nearest whole number?Easy.When rounded to the nearest whole number,0.99=I.Somchow,I thought even though0.99is only0.01away from I,there's still a0.01difference.That means even if two things are only a ltte different,they are still different,so doesn't that make them completely different?My teacher answered my question by presenting another equation(等式):I=0.9,which could also be expressed as1=.99999....repeating itself without ever ending.There was something mysterious but fascinating about the equation.The left side was unchangeable,objective:it contained a number that ended.On the right was something endless, number repeating itself limitless times.Yet,somehow,these two opposed things were connected by an equal sign.Lying in bed,I thought about how much the equation paralleled our existence.The left side of the equation represents that sometimes life itself is so unchangeable and so clear.The concrete,whole number of the day when you were born and the day when you would die.But then there is that gap in between life and death.The right side means a time and space full of limitless possibilities,and endless opportunities into the open future.So that's what life is.Obijective but imaginative.Unchangeable but lniess.Life is an equation with two sides that balances isef out.Sill,we can't ever truly seem to put the perfet words to it.So pssibl numbers can express ideas as eually well as words can.For now,let's leave it at that:1=99999...and live a life like it.24.What does the author emphasize about words in paragraph1?A.Their wide variety.B.Their literary origins.C.Their distinct sounds.D.Their expressive power.25.What made the author find the equation fascinating?A.The repetition of a number.B.The way two different numbers are equal.C.The question the teacher raised.D.The difference between the two numbers.26.Which of the fllowing can replace the underlined word“paralleled”in paragraph6?A.Measured.posed.C.Mirrored.D.Influenced.27.What is a suitable title for the text?A.The Perfect EquationB.Numbers Build EquationsC.An Attractive QuestionD.Words Outperform NumbersC"Why does grandpa have ear hair?"Just a few years ago my child was so curious to know “why"and“how"that we had to cut off her questions five minutes before bedtime.Now a soon-to-be fourth grader,she says that she dislikes school because"it's not fiun to learm."I am shocked.As a scientist and parent,I have done everything I can to promote a love of learning in my children.Where did I go wrong?My child's experience is not unique.Developmental psychologist Susan Engel notes that curiosity defined as“spontaneous(自发的)investigation and eagerness for new information-drops dramatically in children by the fourth grade.In Wonder:Childhood and the Lifelong Love of Science,Yale psychologist Frank C.Keil details the development of wonder一a spontaneous passion to explore,discover,and understand.He takes us on a journey from its early development,when wonder drives common sense and scientific reasoning,through the drop-off in wonder that often occurs,to the trap of life in a society that devalues wonder.As Keil notes,children are particularly rich in wonder while they are rapidly developing causal mechanisms(因果机制)in the preschool and early elementary school years.They are sensitive to the others'knowledge and goals,and they expertly use their desire for questioning. Children's questions,particularly those about""why"and“how,"support the development of causal mechanisms which can be used to help their day-to-day reasoning.Unfortunately,as Keil notes,“adults greatly underestimate young children's causal mechanisms."In the book,Wonder,Keil shows that we can support children's ongoing wonder by playing games with them as partners,encouraging question-asking,and focusing on their abilities to reason and conclude.A decline in wonder is not unavoidable.Keil reminds us that we can accept wonder as a desirable positive quality that exists in everyone.I value wonder deeply,and Wonder has given me hope by proposing a future for my children that will remain wonder-full.28.What is a common problem among fourth graders?A.They upset their parents too often.B.They ask too many strange questions.C.Their love for fun disappears quickly.D.Their desire to learn declines sharply.29.What can be inferred about children's causal mechanisms in paragraph4?A.They control children's sensitivity.B.They slightly change in early childhood.C.They hardly support children's reasoning.D.They develop through children’s questioning.30.How can parents support children's ongoing wonder according to Keil?A.By monitoring their games.B.By welcoming inquiring minds.C.By estimating their abilities.D.By providing reasonable conclusions.31.What is the text?A.A book review.B.A news report.C.A research paper.D.A children's story.DEach year,the world loses about10million hectares of forest一an area about the size of Iceland一because of cutting down trees.At that rate,some scientists predict the world's forests could disappear in100to200years.To handle it,now researchers at Massachusetts Institute of Technology(MIT)have pioneered a technique to generate wood-like plant materials in a lab.This makes it possible to“grow"a wooden product without cutting down trees.In the lab,the researchers first take cells from the leaves of a young plant.These cells are cultured in liquid medium for two days,then moved to another medium which contains nutrients and two different hormones(激素).By adjusting the hormone levels,the researchers can tune the physical and mechanical qualities of the cells.Next,the researchers use a3D printer to shape the cell-based material,and let the shaped material grow in the dark for three months.Finally, the researchers dehydrate(使脱水)the material,and then evaluate its qualities.They found that lower hormone levels lead to plant materials with more rounded,open cells of lower density(密度),while higher hormone levels contribute to the growth of plant materials with smaller but denser cell structures.Lower or higher density of cell structures makes the plant materials softer or more rigid,helping the materials grow with different wood-like characteristics.What's more,it's to be noted that the research process is about100times faster than the time it takes for a tree to grow to maturity!Research of this kind is ground-breaking.“This work demonstrates the great power of a technology,"says lead researcher,Jeffrey Berenstain."The real opportunity here is to be at its best with what you use and how you use it.This technology can be tuned to meet the requirements you give about shapes,sizes,rigidity,and forms.It enables us to'grow’any wooden product in a way that traditional agricultural methods can't achieve."32.Why do researchers at MIT conduct the research?A.To grow more trees.B.To protect plant diversity.C.To reduce tree losses.D.To predict forest disappearance.33.What does paragraph2mainly tell us about the lab research?A.Its theoretical basis.B.Its key procedures.C.Its scientific evidence.D.Its usual difficulties.34.What does the finding suggest about the plant materials?A.The hormone levels affect their rigidity.B.They are better than naturally grown plants.C.Their cells'shapes mainly rely on their density.D.Their growth speed determines their characteristics.35.Why is the research ground-breaking according to Berenstain?A.It uses new biological materials in lab experiments.B.It revolutionizes the way to make wooden products.C.It challenges traditional scientific theories in forestry.D.It has a significant impact on worldwide plant growth.第二节(共5小题;每小题2.5分，满分12.5分)阅读下面短文，从短文后的选项中选出可以填入空白处的最佳选项。

环境与健康杂志2010年4月第27卷第4期J Environ Health,April 2010,Vol．27,No．4【论著】文章编号：1001-5914（2010）04-0346-03防晒化妆品中5种紫外吸收剂的超高效液相色谱测定法卢晓蕊1，韩仰学2，霍任锋1，沈虹1摘要：目的建立防晒化妆品中2-羟基-4-甲氧基二苯酮、水杨酸苯酯、对二甲基氨基苯甲酸-2-乙基己酯、2，2，4，4-四羟基二苯甲酮、2-羟基-4-甲氧基二苯甲酮-5-磺酸5种紫外吸收剂同时测定的超高效液相色谱（UPLC ）法。

方法样品以甲醇为溶剂，经超声提取，以乙腈∶水=70∶30（V /V ）为流动相进行分离，流量为0.3ml/min ，检测波长310nm 。

结果在0～25mg/L 的线性范围内，5种紫外吸收剂所得的回归方程均呈较好的线性关系，相关系数>0.999，检出限为4～6mg/L ，最低检出浓度为0.01%～0.015%。

该方法的平均回收率为98.35%～102.75%，RSD 为0.44%～1.73%。

结论该方法简便、准确、快速，适用于同时测定防晒化妆品中5种紫外吸收剂的含量。

关键词：色谱法，液相；化妆品；紫外吸收剂中图分类号：O657.6文献标识码：ADetermination of Five Kinds of Ultraviolet Absorbents in Cosmetics by Ultra Performance Liquid Chromatography LU Xiao -rui ，HAN Yang -xue ，HUO Ren -feng ，et al .Beijing Products Quality Supervision and Inspection Institute ，Beijing 100026，ChinaCorresponding auther ：SHEN Hong ，Tel ：（010）84628245Abstract ：Objective To establish an ultra performance liquid chromatography （UPLC ）method for simultaneous determination of five kinds of ultraviolet absorbents in cosmetics,benzophenone -4and benzophenone -5,etc.Methods The cosmetic samples were extracted with methanol ，using acetonitrile/water=70∶30（V /V ）as mobile phase at the flow rate of 0.3ml/min and detected at the wavelength of 310nm.Results There was a good linear relationship over the range of 0-25mg/L of five ultraviolet absorbents ，r >0.999，the limits of detection of five ultraviolet absorbents were 4to 6mg/L and the minimum detectable concentration was 0.01%-0.015%.The rates of recovery for this method ranged from 98.35%to 102.75%and the relative standard deviations of this method were 0.44%to 1.73%.Conclusion The method is simple ，rapid ，accurate and applicable to simultaneous determination of the five ultraviolet absorbents in cosmetics.Key words:Chromatography ，liquid ；Cosmetics ；Ultraviolet absorbents 作者单位：1.北京市产品质量监督检验所化工产品检测室（北京100026）；2.上海海洋大学水产与生命学院（上海201306）作者简介：卢晓蕊（1983-），女，硕士研究生，从事化妆品检测等方面的研究。

《孟德尔随机化研究指南》中英文版全文共3篇示例，供读者参考篇1Mendel's Randomization Research GuideIntroductionMendel's Randomization Research Guide is a comprehensive resource for researchers in the field of genetics who are interested in incorporating randomization into their study designs. Developed by Dr. Gregor Mendel, a renowned geneticist known for his pioneering work on the inheritance of traits in pea plants, this guide provides a detailed overview of the principles and methods of randomization in research.Key ConceptsRandomization is a crucial tool in scientific research that helps to eliminate bias and increase the validity of study findings. By randomly assigning participants to different treatment groups or conditions, researchers can ensure that the groups are comparable and that any observed differences are truly due to the intervention being studied.The guide covers a range of topics related to randomization, including the importance of random assignment, the different types of randomization methods, and the potential pitfalls to avoid when implementing randomization in a study. It also provides practical guidance on how to design and conduct randomized experiments, including tips on sample size calculation, randomization procedures, and data analysis methods.Benefits of RandomizationRandomization offers several key benefits for researchers, including:1. Increased internal validity: Random assignment helps to ensure that the groups being compared are equivalent at the outset of the study, reducing the risk of confounding variables influencing the results.2. Improved generalizability: By minimizing bias and increasing the reliability of study findings, randomization enhances the external validity of research findings and allows for more generalizable conclusions to be drawn.3. Ethical considerations: Randomization is considered a fair and unbiased method for allocating participants to differentgroups, helping to ensure that all participants have an equal chance of receiving the intervention being studied.Practical ApplicationsThe guide provides practical examples of how randomization can be applied in research studies, ranging from clinical trials to observational studies. For example, researchers conducting a randomized controlled trial may usecomputer-generated randomization software to assign participants to different treatment groups, while researchers conducting an observational study may use stratified random sampling to ensure that key variables are evenly distributed across study groups.In addition, the guide outlines best practices for implementing randomization in research studies, including the importance of blinding participants and investigators to group assignment, documenting the randomization process, and conducting sensitivity analyses to assess the robustness of study findings.ConclusionIn conclusion, Mendel's Randomization Research Guide is an invaluable resource for researchers seeking to incorporaterandomization into their study designs. By following the principles and methods outlined in the guide, researchers can enhance the validity and reliability of their research findings, ultimately leading to more impactful and meaningful contributions to the field of genetics.篇2Mendel Randomization Research GuideIntroduction:The Mendel randomization research guide is a comprehensive manual that provides researchers with detailed instructions on using Mendelian randomization (MR) in their studies. MR is a statistical method that uses genetic information to investigate causal relationships between exposures, known as risk factors, and outcomes, such as diseases or health-related outcomes. This guide aims to help researchers understand the principles of MR, design robust studies, and interpret their results accurately.Key Sections:1. Introduction to Mendelian Randomization:- Overview of MR as a method for assessing causality- Explanation of the assumptions underlying MR studies- Discussion of the advantages and limitations of MR compared to traditional observational studies2. Study Design:- Selection of genetic instruments for exposure variables- Matching of genetic instruments to outcome variables- Consideration of potential biases and confounding factors- Power calculations and sample size considerations3. Data Analysis:- Methods for instrumental variables analysis- Sensitivity analyses to assess the robustness of results- Techniques for handling missing data and population stratification4. Interpretation of Results:- Methods for assessing causality using MR- Consideration of biases and limitations in MR studies- Implications of findings for public health and clinical practiceCase Studies:The Mendel randomization research guide includes several case studies that demonstrate the application of MR in various research settings. These case studies illustrate the steps involved in designing MR studies, selecting appropriate genetic instruments, analyzing data, and interpreting results. Researchers can use these examples as a guide for conducting their own MR studies and interpreting their findings.Conclusion:The Mendel randomization research guide is a valuable resource for researchers interested in using MR to investigate causal relationships in health research. By following the guidelines outlined in this manual, researchers can design rigorous MR studies, analyze their data accurately, and draw meaningful conclusions about the impact of risk factors on health outcomes. This guide will help advance the field of epidemiology and pave the way for more robust and reliable research in the future.篇3Mendel Randomization Research GuideIntroductionThe Mendel Randomization Research Guide is a comprehensive resource aimed at providing researchers with the necessary tools and techniques to conduct randomized studies in the field of genetics. The guide covers various aspects of Mendel randomization, a method that uses genetic variants as instruments for studying the causal effects of exposures or interventions on outcomes.Key Concepts1. Mendelian Randomization: Mendelian randomization is a technique that uses genetic variants as instrumental variables to study the causal relationship between an exposure and an outcome. By leveraging genetic variability, researchers can overcome confounding and reverse causation biases that often plague traditional observational studies.2. Instrumental Variables: Instrumental variables are genetic variants that are associated with the exposure of interest but do not have a direct effect on the outcome, except through the exposure. These genetic variants serve as instruments for estimating the causal effect of the exposure on the outcome.3. Bias Minimization: Mendel randomization helps minimize bias in observational studies by mimicking the random assignment of exposures in a controlled experiment. By usinggenetic variants as instruments, researchers can ensure that any observed associations are less likely to be influenced by confounding factors.Guide Contents1. Study Design: The guide provides detailed information on how to design Mendelian randomization studies, including selecting genetic instruments, conducting power calculations, and assessing instrument validity.2. Data Collection: Researchers will learn about the various data sources available for Mendel randomization studies, such as genome-wide association studies, biobanks, and electronic health records.3. Analysis Methods: The guide covers statistical techniques for analyzing Mendelian randomization data, includingtwo-sample MR, inverse variance-weighted regression, and sensitivity analyses.4. Reporting Guidelines: Researchers will find guidelines on how to report Mendelian randomization studies in a clear and transparent manner, following best practices in scientific research.ConclusionThe Mendel Randomization Research Guide offers a comprehensive overview of the principles, methods, and applications of Mendelian randomization in genetic research. By following the guidelines outlined in the guide, researchers can conduct rigorous and unbiased studies that provide valuable insights into the causal effects of exposures on health outcomes.。

再论中介模型滥⽤：如何规范地实施因果中介效应分析因果中介效应估计、敏感性分析、⼯具变量模型。

近年来，⼤量的经济学论⽂滥⽤中介效应模型，参考⽂献是⼀遍中⽂⼼理学论⽂，特别以硕⼠论⽂居多，引起严肃经济学者的警觉和批评。

在这个⽅程组中有很多的问题存在：y=a+bx+u (1)m=a1x+u1 (2)y=a2x+b2m+u2 (3）很显然（1）式中⾄少遗漏了中介变量m，则导致严重内⽣性问题，内⽣性导致b的估计是有偏的，b都估计不对，何谈后⾯的因果效应和机制分析的识别？且不说有没有考虑三个⼦⽅程的内⽣性问题了！令⼈悲哀和⽆免，其实只需要基本的初等计量经济学知识！本推⽂将介绍在因果分析框架下中介分析模型。

此外，管理学的调节效应其实就是规范实证经济学⾥⾯的交互项模型，即相关异质性因果效应分析：即将开幕的STATA前沿培训精讲：带异质性处理效应的双向固定效应估计|从精确断点、模糊断点估计的实际操作|弱⼯具变量稳健推断异质性分析、机制分析的内容可选择学习：即将开班 | 结构模型、Stata实证前沿、Python数据挖掘暑假⼯作坊当然，⽐较合理地机制分析是基于理论框架的科学分析，这也可以在以上暑假⼯作坊课程中的结构估计部分学习之，其也提供⽂本分析的内容。

欢迎咨询！Causal mediation analysisRaymond Hicks,Niehaus Center for Globalization and GovernancePrinceton University,Princeton, NJ,rhicks@Dustin Tingley,Department of Government,Harvard UniversityCambridge, MA,dtingley@Abstract. Estimating the mechanisms that connect explanatory variables with the explained variable, also known as “mediation analysis,” is central to a variety of social-science fields, especially psychology, and incre epidemiology.Recent work on the statistical methodology behind mediation analysis points to limitations in earlier methods. We implement in Stata computational approaches based on recent developments in the sta analysis. In particular, we provide functions for the correct calculation of causal mediation effects using several different types of parametric models, as well as the calculation of sensitivity analyses for violations to the required for interpreting mediation results causally.摘要：估计解释变量与被解释变量之间的联系机制，也被称为“中介分析”，是各种社会科学领域的核⼼，尤其是⼼理学，并逐渐成为流⾏病学等领域的核⼼。

Chapter 3Hazard Analysis Typesand Techniques3.1TYPES AND TECHNIQUESHazard analyses are performed to identify hazards,hazard effects,and hazard causal factors.Hazard analyses are used to determine system risk and thereby ascertain the significance of hazards so that safety design measures can be established to eliminate or mitigate the hazard.Analyses are performed to systematically examine the system,subsystem,facility,components,software,personnel,and their interrelationships.There are two categories of hazard analyses:types and techniques.Hazard analy-sis type defines an analysis category (e.g.,detailed design analysis),and technique defines a unique analysis methodology (e.g.,fault tree analysis).The type estab-lishes analysis timing,depth of detail,and system coverage.The technique refers to a specific and unique analysis methodology that provides specific results.System safety is built upon seven basic types,while there are well over 100different tech-niques available.1In general,there are several different techniques available for achieving each of the various types.The overarching distinctions between type and technique are summarized in Table 3.1.Hazard analysis type describes the scope,coverage,detail,and life-cycle phase timing of the particular hazard analysis.Each type of analysis is intended to provide a time-or phase-dependent analysis that readily identifies hazards for a particular design phase in the system development life cycle.Since more detailed design 1Refer to the System Safety Analysis Handbook published by the System Safety Society.31Hazard Analysis Techniques for System Safety ,by Clifton A.Ericson,IICopyright #2005John Wiley &Sons,Inc.and operation information is available as the development program progresses,so in turn more detailed information is available for a particular type of hazard analysis.The depth of detail for the analysis type increases as the level of design detail progresses.Each of these analysis types define a point in time when the analysis should begin,the level of detail of the analysis,the type of information available,and the analysis output.The goals of each analysis type can be achieved by various analysis techniques.The analyst needs to carefully select the appropriate techniques to achieve the goals of each of the analysis types.There are seven hazard analysis types in the system safety discipline:1.Conceptual design hazard analysis type (CD-HAT)2.Preliminary design hazard analysis type (PD-HAT)3.Detailed design hazard analysis type (DD-HAT)4.System design hazard analysis type (SD-HAT)5.Operations design hazard analysis type (OD-HAT)6.Health design hazard analysis type (HD-HAT)7.Requirements design hazard analysis type (RD-HAT)An important principle about hazard analysis is that one particular hazard analy-sis type does not necessarily identify all the hazards within a system;identification of hazards may take more than one analysis type (hence the seven types).A corollary to this principle is that one particular hazard analysis type does not necessarily identify all of the hazard causal factors;more than one analysis type may be required.After performing all seven of the hazard analysis types,all hazards and causal factors should have been identified;however,additional hazards may be discovered during the test program.Figure 3.1conveys the filter concept behind the seven hazard analysis types.In this concept,each hazard analysis type acts like a filter that identifies certain types of hazards.Each successive filter serves to identify hazards missed by the pre-vious filter.The thick dark arrows at the top of the filter signify hazards existing in the system design.When all of the hazard analysis types have been applied,the onlyTABLE 3.1Hazard Analysis Type vs.TechniqueTypeTechnique .Establishes where,when,and what to analyze..Establishes how to perform the analysis..Establishes a specific analysis task at specific time in program life cycle..Establishes a specific and unique analysis methodology..Establishes what is desired from the analysis..Provides the information to satisfy the intent of the analysis type..Provides a specific design focus.32HAZARD ANALYSIS TYPES AND TECHNIQUESknown hazards remaining have been reduced to an acceptable level of risk,denoted by the smaller thin e of all seven hazards analysis types is critical in iden-tifying and mitigating all hazards and reducing system residual risk.Each hazard analysis type serves a unique function or purpose.For a best practice system safety program (SSP),it is recommended that all seven of these hazard analysis types be applied;however,tailoring is permissible.If tailoring is utilized,the specifics should be spelled out in the system safety management plan (SSMP)and /or the system safety program plan (SSPP).Figure 3.2depicts the relationship between hazard types and techniques.In this relationship,the seven hazard analysis types form the central focus for SSP hazard analysis.There are many different analysis techniques to select from when perform-ing the analysis types,and there are many different factors that must go into the hazard analysis,such as the system life-cycle stages of concept,design,test,manu-facture,operation,and disposal.The system modes,phases,and functions must be considered.The system hardware,software,firmware,human interfaces,and environmental aspects must also be considered.Some textbooks refer to the seven types as preliminary hazard list (PHL),pre-liminary hazard analysis (PHA),subsystem hazard analysis (SSHA),system hazard analysis (SHA),operating and support hazard analysis (O&SHA),health hazard analysis (HHA),and safety requirement /criteria analysis (SRCA).These names are,however,the same names as the basic hazard analysis techniques established by MIL-STD-882,versions A,B,and C.The concept of analysis types is a good concept,but having types and techniques with the same name is somewhat confus-ing.The approach recommended in this book ensures there are no common names between types and techniques,thus avoiding muchconfusion.HAZARDSFigure 3.1Hazard filters.3.1TYPES AND TECHNIQUES 333.2DESCRIPTION OF HAZARD ANALYSIS TYPES 3.2.1Conceptual Design Hazard Analysis Type (CD-HAT)The CD-HAT is a high-level (low level of detail)form of hazard analysis that identifies top-level hazards that can be recognized during the conceptual design phase.The CD-HAT is the first analysis type performed and is the starting point for all subsequent hazard analyses.The CD-HAT provides a basis for initially estimating the overall SSP effort.The purpose of the CD-HAT is to compile a list of hazards very early in the pro-duct or system development life cycle to identify potentially hazardous areas.These hazardous areas identify where management should place design safety emphasis.The CD-HAT searches for hazards that may be inherent in the design or operational concept.It is a brainstorming,“what-if”analysis.A hazard list is generated from the brainstorming session,or sessions,where everything conceivable is considered and documented.The topics include review of safety experience on similar systems,hazard checklists,mishap /incident hazard tracking logs,safety lessons learned,and so forth to identify possible hazards.The key to a successful SSP is involvement early in the development program,beginning during conceptual design.The CD-HAT is started when the concept definition for a product or system begins and carries into the preliminary design phase.It is performed early in the program life cycle in order to influence design con-cepts and decisions for safety as early as possible.The CD-HAT is the first analysis type performed and precedes the PD-HAT since it provides input for the PD-HAT.Preliminary Hazard List (PHL)Preliminary Hazard Analysis (PHA)Safety Requirements/Criteria Analysis (SRCA)Subsystem Hazard Analysis (SSHA)System Hazard Analysis (SHA)Operations & Support Hazard Analysis (O&SHA)Health Hazard Assessment (HHA)Fault Tree Analysis (FTA)Failure Modes and Effects Analysis (FMEA)Fault Hazard Analysis (FaHA)Functional Hazard Analysis (FuHA)Sneak Circuit Analysis (SCA)Software Sneak Circuit Analysis (SWSCA)Petri Net Analysis (PNA)Markov Analysis (MA)Barrier Analysis (BA)Bent Pin Analysis (BPA)Threat Hazard Assessment (THA)Hazard and Operability Study (HAZOP)Cause Consequence Analysis (CCA)Common Cause Failure Analysis (CCFA)Management Oversight and Risk T ree (MORT)Software Hazard Assessment (SWHA) •••Analysis TechniquesAnalysis Types CD-HAT PD-HA T DD-HAT SD-HA T OD-HAT HD-HAT RD-HATFigure 3.2Type–technique relationship.34HAZARD ANALYSIS TYPES AND TECHNIQUES3.2DESCRIPTION OF HAZARD ANALYSIS TYPES35If the CD-HAT is not performed during concept definition,it should be per-formed prior to,and as part of,any PD-HAT effort since it is an essential precursor to the PD-HAT.Once the initial CD-HAT is completed and documented,it is rarely updated as additional hazard identification analysis is achieved via the PD-HAT.In general,the CD-HAT supports the system design review(SDR),and CD-HAT effort ends at the start of the PD-HAT.The following are the basic requirements of a comprehensive CD-HAT:1.Will be applied during the design concept phase of system development.2.Will be a high-level analysis(low level of detail)based on conceptual designinformation.3.Will identify system hazards and potential mishaps.4.Will consider hazards during system test,manufacture,operation,mainten-ance,and disposal.5.Will consider system hardware,software,firmware,human interfaces,andenvironmental aspects.Input information for the CD-HAT analysis type includes everything that is avail-able during conceptual design.Experience has shown that generally the CD-HAT can be performed utilizing the following types of information:1.Design concept2.Statement of work(SOW),specification,drawings(if available)3.Preliminary(conceptual)indentured equipment list4.Preliminary(conceptual)functions list5.Energy sources in the system6.Hazard checklists(generic)7.Lessons learned(similar systems)The primary purpose of the CD-HAT is to generate a list of system-level hazards, which can be used as an initial risk assessment and as the starting point for the sub-sequent hazard analysis types.As such,the following information is typically output from the CD-HAT analysis:1.System hazards2.Top-level mishaps(TLMs)rmation to support the PD-HAT analysis3.2.2Preliminary Design Hazard Analysis Type(PD-HAT)The PD-HAT is a preliminary level form of analysis that does not go into extensive detail;it is preliminary in nature.The PD-HAT is performed to identify system-level hazards and to obtain an initial risk assessment of a system design.It is performed36HAZARD ANALYSIS TYPES AND TECHNIQUESearly,during the preliminary design phase,in order to affect design decisions as early as possible to avoid future costly design changes.The PD-HAT is the basic hazard analysis that establishes the framework for all of the follow-on hazard analyses.It provides a preliminary safety engineering evalu-ation of the design in terms of potential hazards,causal factors,and mishap risk. The intent of the PD-HAT is to recognize the hazardous system states and to begin the process of controlling hazards identified by the CD-HAT.As the design progresses in detail,more detailed analyses are performed to facilitate the elimin-ation or mitigation of all hazards.Identification of safety critical functions(SCFs)and TLMs is a key element of the PD-HAT.The specific definition of what constitutes classification as safety critical (SC)is generally program specific,as different types of systems may warrant differ-ent definitions based on the hazardous nature of the system.The PD-HAT should be started during the design conceptual stage(after the CD-HAT)and continued through preliminary design.If the PD-HAT is not initiated during conceptual design,it should be initiated with the start of preliminary design. It is important that safety considerations identified in the PD-HAT are included in trade studies and design alternatives as early as possible in the design process.Work on the PD-HAT usually concludes when the DD-HAT is initiated.In gen-eral,the PD-HAT supports all preliminary design reviews.The PD-HAT may also be used on an existing operational system for the initial examination of proposed design changes to the system.The following are the basic requirements of a comprehensive PD-HAT:1.Will be applied during the design concept and preliminary design phases ofsystem development.2.Will focus on all system hazards resulting from the preliminary designconcept and component selection.3.Will be a high-to medium-level analysis(low to medium level of detail)thatis based on preliminary design information.4.Will identify hazards,potential mishaps,causal factors,risk,and SCFs.It willidentify applicable safety guidelines,requirements,principles,and precepts to mitigate hazards.It will also provide recommendations to mitigate hazards.5.Will consider hazards during system test,manufacture,operation,mainten-ance,and disposal.6.Will consider system hardware,software,firmware,human interfaces,andenvironmental aspects.Input information for the PD-HAT consists of the preliminary design information that is available during the preliminary design development phase.Typically the following types of information are available and utilized in the PD-HAT:1.Results of the CD-HAT analysis2.SOW3.2DESCRIPTION OF HAZARD ANALYSIS TYPES373.System specification4.Design drawings and sketches5.Preliminary indentured equipment list6.Functionalflow diagrams of activities,functions,and operations7.Concepts for operation,test,manufacturing,storage,repair,and transportation8.Energy sources9.Hazard checklists(generic)10.Lessons learned from experiences of similar previous programs or activities11.Failure modes review12.Safety guidelines and requirements from standards and manualsThe primary purpose of the PD-HAT is to perform a formal analysis for identify-ing system-level hazards and evaluating the associated risk levels.As such,the following information is typically output from the PD-HAT:1.System-level hazards2.Hazard effects and mishaps3.Hazard causal factors(to subsystem identification)4.SCFs5.TLMs6.Safety design criteria,principles,and precepts for design guidance in hazardmitigation7.Risk assessment(before and after design safety features for hazardmitigation)8.Safety recommendations for eliminating or mitigating the hazardsrmation to support DD-HAT,SD-HAT,and OD-HAT analyses3.2.3Detailed Design Hazard Analysis Type(DD-HAT)The DD-HAT is a detailed form of analysis,performed to further evaluate hazards from the PHA with new detailed design information.The DD-HAT also evaluates the functional relationships of components and equipment comprising each sub-system.The analysis will help identify all components and equipment whose performance degradation or functional failure could result in hazardous conditions. Of particular concern is the identification of single-point failures(SPFs).The DD-HAT is also used to identify new hazards that can be recognized from the detailed design information that is available and to identify the hazard causal factors of specific subsystems and their associated risk levels.The DD-HAT is an analysis of the detailed design and can therefore run from the start of detailed design through completion offinal manufacturing drawings.Once the initial DD-HAT is completed and documented,it is not generally updated and enhanced,except for the evaluation of design changes.38HAZARD ANALYSIS TYPES AND TECHNIQUESThe following are the basic requirements of a comprehensive DD-HAT analysis:1.Will be a detailed analysis at the subsystem and component level.2.Will be applied during the detailed design of the system.3.Will identify hazards,resulting mishaps,causal factors,risk,and SCFs.It willalso identify applicable safety recommendations for hazard mitigation.4.Will consider hazards during system test,manufacture,operation,mainten-ance,and disposal.5.Will consider system hardware,software,firmware,human interfaces,andenvironmental aspects.Input information for the DD-HAT analysis consists of all detailed design data. Typically the following types of information are available and utilized in the DD-HAT:1.PD-HAT analysis results2.System description(design and functions)3.Detailed design information(drawings,schematics,etc.)4.Indentured equipment list5.Functional block diagrams6.Hazard checklistsThe primary purpose of the DD-HAT is to evaluate the detailed design for hazards and hazard causal factors and the associated subsystem risk levels.As such,the following information is typical output from the DD-HAT:1.Subsystem hazards2.Detailed causal factors3.Risk assessment4.Safety critical subsystem interfaces5.Safety design recommendations to mitigate hazards6.Special detailed analyses of specific hazards using special analysis techniquessuch as fault tree analysis(FTA)rmation to support the RD-HAT and SD-HAT analyses3.2.4System Design Hazard Analysis Type(SD-HAT)The SD-HAT assesses the total system design safety by evaluating the integrated system design.The primary emphasis of the SD-HAT,inclusive of both hardware and software,is to verify that the product is in compliance with the specified safety requirements at the system level.This includes compliance with acceptable mishap risk levels.The SD-HAT examines the entire system as a whole by integrating the essential outputs from the DD-HAT analyses.Emphasis is placed on the interactions and the interfaces of all the subsystems as they operate together.3.2DESCRIPTION OF HAZARD ANALYSIS TYPES39The SD-HAT provides determination of system risks in terms of hazard severity and hazard probability.System hazards are evaluated to identify all causal factors, including hardware,software,firmware,and human interaction.The causal factors may involve many interrelated fault events from many different subsystems.Thus, the SD-HAT evaluates all the subsystem interfaces and interrelationships for each system hazard.The SD-HAT is system oriented,and therefore it usually begins during prelimi-nary design and is complete by the end offinal design,except for closure of all hazards.The SD-HAT isfinalized at completion of the test program when all hazards have been tested for closure.SD-HAT documentation generally supports safety decisions for commencement of operational evaluations.The SD-HAT should be updated as a result of any system design changes,including software andfirm-ware design changes to ensure that the design change does not adversely affect system mishap risk.The following are the basic requirements of a comprehensive SD-HAT analysis:1.Will be applied primarily during the detailed design phase of system develop-ment;it can be initiated during preliminary design.2.Is a detailed level of analysis that provides focus from an integrated systemviewpoint.3.Will be based on detailed andfinal design information.4.Will identify new hazards associated with the subsystem interfaces.5.Will consider hazards during system test,manufacture,operation,mainten-ance,and disposal.6.Will consider system hardware,software,firmware,human interfaces,andenvironmental aspects.Typically the following types of information are available and utilized in the SD-HAT analysis:1.PD-HAT,DD-HAT,RD-HAT,OD-HAT,and other detailed hazard analyses2.System design requirements3.System description(design and functions)4.Equipment and function indenture lists5.System interface specifications6.Test dataThe primary purpose of the SD-HAT analysis is to perform a formal analysis for identifying system-level hazards and evaluating the associated risk levels.As such, the following information is typically output from the SD-HAT:1.System interface hazards2.System hazard causal factors(hardware,software,firmware,human inter-action,and environmental)40HAZARD ANALYSIS TYPES AND TECHNIQUES3.Assessment of system risk4.Special detailed analyses of specific hazards using special analysis techniquessuch as FTArmation to support the safety assessment report(SAR)3.2.5Operations Design Hazard Analysis Type(OD-HAT)The OD-HAT analysis evaluates the operations and support functions involved with the system.These functions include use,test,maintenance,training,storage, handling,transportation,and demilitarization or disposal.The OD-HAT analysis identifies operational hazards that can be eliminated or mitigated through design fea-tures and through modified operational procedures when necessary.The OD-HAT analysis considers human limitations and potential human errors(human factors). The human is considered an element of the total system,receiving inputs and initiating outputs.The OD-HAT analysis is performed when operations information becomes avail-able and should start early enough to provide inputs to the design.The OD-HAT should be completed prior to the conduct of any operating and support functions.The following are the basic requirements of a comprehensive OD-HAT analysis:1.Will be performed during the detailed design phases of system developmentwhen the operating and support procedures are being written.2.Will focus on hazards occurring during operations and support.3.Will provide an integrated assessment of the system design,related equip-ment,facilities,operational tasks,and human factors.4.Will be a detailed analysis based onfinal design information.5.Will identify hazards,potential mishaps,causal factors,risk and safetycritical factors,applicable safety requirements,and hazard mitigation recommendations.6.Will consider hazards during system use,test,maintenance,training,storage,handling,transportation,and demilitarization or disposal.The following types of information are utilized in the OD-HAT:1.PD-HAT,DD-HAT,SD-HAT,and any other applicable hazard analyses2.Engineering descriptions/drawings of the system,support equipment,andfacilities3.Available procedures and operating manuals4.Operational requirements,constraints,and required personnel capabilities5.Human factors engineering data and reports6.Lessons learned,including human factors7.Operational sequence diagrams3.2DESCRIPTION OF HAZARD ANALYSIS TYPES41The OD-HAT focus is on operating and support tasks and procedures.The following information is typically available from the OD-HAT:1.Task-oriented hazards(caused by design,software,human,timing,etc.)2.Hazard mishap effect3.Hazard causal factors(including human factors)4.Risk assessment5.Hazard mitigation recommendations and derived design safety requirements6.Derived procedural safety requirements7.Cautions and warnings for procedures and manuals8.Input information to support the SD-HAT analysis3.2.6Human Design Hazard Analysis Type(HD-HAT)The HD-HAT analysis is intended to systematically identify and evaluate human health hazards,evaluate proposed hazardous materials,and propose measures to eliminate or control these hazards through engineering design changes or protective measures to reduce the risk to an acceptable level.The HD-HAT assesses design safety by evaluating the human health aspects involved with the system.These aspects include manufacture,use,test, maintenance,training,storage,handling,transportation,and demilitarization or disposal.The HD-HAT concentrates on human health hazards.The HD-HAT is started during preliminary design and continues to be performed as more information becomes available.The HD-HAT should be completed and system risk known prior to the conduct of any of the manufacturing,test,or operational phases.The following are the basic requirements of a comprehensive HD-HAT analysis:1.Will be applied during the preliminary and detailed design phases of systemdevelopment.2.Will focus on the human environment within the system.3.Will be a detailed analysis based on system design and operational tasksaffecting the human environment.4.Will identify hazards,potential mishaps,causal factors,risk and safety criticalfactors,and applicable safety requirements.5.Will consider human health hazards during system test,manufacture,oper-ation,maintenance,and demilitarization or disposal.Consideration should include,but is not limited to,the following:a.Materials hazardous to human health(e.g.,material safety data sheets)b.Chemical hazardsc.Radiological hazardsd.Biological hazards42HAZARD ANALYSIS TYPES AND TECHNIQUESe.Ergonomic hazardsf.Physical hazardsTypically the following types of information are available and utilized in the HD-HAT analysis:1.CD-HAT,PD-HAT,DD-HAT,SD-HAT,OD-HAT,and any other applicabledetailed hazard analyses2.Materials and compounds used in the system production and operation3.Material safety data sheets4.System operational tasks and procedures,including maintenance procedures5.System designThe following information is typically available from the HD-HAT analysis:1.Human health hazards2.Hazard mishap effects3.Hazard causal factors4.Risk assessment5.Derived design safety requirements6.Derived procedural safety requirements(including cautions,warnings,andpersonal protective equipment)7.Input information for the Occupational Safety and Health Administration(OSHA)and environmental evaluationsrmation to support the OD-HAT and SD-HAT analyses3.2.7Requirements Design Hazard Analysis Type(RD-HAT)The RD-HAT is a form of analysis that verifies and validates the design safety requirements and ensures that no safety gaps exist in the requirements.The RD-HAT applies to hardware,software,firmware,and test requirements.Since the RD-HAT is an evaluation of design and test safety requirements,it is performed during the design and test stages of the development program.The RD-HAT can run from mid-preliminary design through the end of testing.Safety design requirements are generated from three sources:(1)the system specification,(2)generic requirements from similar systems,subsystems,and processes,and(3)requirements derived from recommendations to mitigate ident-ified system-unique hazards.The intent of the RD-HAT is to ensure that all of the appropriate safety requirements are included within the design requirements and that they are verified and validated through testing,analysis,or inspection.Appli-cable generic system safety design requirements are obtained from such sources as federal,military,national,and industry regulations,codes,standards,specifica-tions,guidelines,and other related documents for the system under development.3.2DESCRIPTION OF HAZARD ANALYSIS TYPES43The RD-HAT supports closure of identified hazards.Safety requirements levied against the design to mitigate identified hazards must be verified and validated before a hazard in the hazard tracking system can be closed.The RD-HAT provides a means of traceability for all safety requirements,verifying their implementation and validating their success.The RD-HAT is an evolving analysis that is performed over a period of time, where it is continually updated and enhanced as more design and test information becomes available.The RD-HAT is typically performed in conjunction with the PD-HAT,DD-HAT,SD-HAT,and OD-HAT analyses.The RD-HAT should be complete at the end of testing.The following are the basic requirements of a comprehensive RD-HAT analysis:1.Will be applied from the preliminary design phases through testing of thesystem.2.Will focus on safety requirements intended to eliminate and/or mitigateidentified hazards.3.Will be a detailed analysis based on detailed design requirements and designinformation.4.Will ensure that all identified hazards have suitable safety requirements toeliminate and/or mitigate the hazards.5.Will ensure that all safety requirements are verified and validated throughanalysis,testing,or inspection.Typically the following types of information are available and utilized in the RD-HAT:1.Hazards without mitigating safety requirements2.Design safety requirements(hardware,software,firmware)3.Test requirements4.Test results5.Unverified safety requirementsThe primary purposes of the RD-HAT are to establish traceability of safety requirements and to assist in the closure of mitigated hazards.The following infor-mation is typically output from the RD-HAT:1.Traceability matrix of all safety design requirements to identified hazards2.Traceability matrix of all safety design requirements to test requirements andtest results3.Identification of new safety design requirements and tests necessary to covergaps discovered by items1and2above4.Data supporting closure of hazards。

社會學研究方法課程綱要(暫定)課程名稱：社會學研究方法學分數：3授課時間：周四上午第5-6節（93學年度下學期）授課教室：綜合270837任課教師：關秉寅研究室：綜合院館南棟16樓271662室聯絡方式：校內分機51662；E-mail: soci1005@.tw教學網站：.tw/~soci1005課程簡介本課程為碩士班學生必修課程。

其基本目的是幫助研究生準備研究所學習最重要的項目─論文研究。

這門課程的基本理念是認為經驗研究是社會學知識發展的必要基礎。

但是，這門課程並非重複大學部的研究法課程。

如果大學部的研究法課程是在學習運用及操作實際研究方法的步驟與技巧，而研究所的方法論課程是談研究方法及程序應建立在何種前提與原則上，才能使我們獲得有效的或什麼樣之知識的話，本課程的定位可看成是處在這兩者中間，但偏向方法論的位置。

本課程將著重探討推論現象間的關係（特別是因果關係），由部分推論到整體（即抽樣方面的考量），以及如何適當表述現象（即概念化與測量）等相關議題。

本課程將只就一些常見的量化及質化研究方法的基本原則，做比較深入的討論，因此本課程不是替代相關特定研究方法之課程。

依據授課教師的能力與興趣，本課程會比較偏重量化研究方法的探討。

上課方式本課程的研習主要是透過閱讀在重要期刊上發表的研究論文，以及探討研究方法之書籍的篇章，來深入瞭解經驗研究的過程。

上課時同學應針對各週指定及參考閱讀材料做集體討論。

因此，同學應自行研讀各週所安排的閱讀材料，並準時出席及積極參與討論。

課程要求為達成本課程之目的，修習本課程的同學須完成以下兩種作業：1、每週閱讀之短評：這個作業是就各週指定之「指定閱讀」寫一至二頁的短評，以及自選一篇「參考閱讀」，寫一至二頁的摘要。

這個作業的目的是確保同學在上課前，已經做好閱讀及參與討論的準備。

因此，這個作業要在每週上課前完成，並影印帶到課堂給其他同學參考。

「必讀材料」之短評的內容應包括兩個部分。

Econometrics 专业词汇中英文对照（按课件顺序）Ch1-3Causal effects：因果影响，指的是当x变化时，会引起y的变化；Elasticity：弹性；correlation (coefficient) 相关（系数），相关系数没有单位，unit free；estimation：估计；hypothesis testing：假设检验；confidence interval：置信区间；difference-in-means test：均值差异检验，即检验两个样本的均值是否相同；standard error：标准差；statistical inference：统计推断；Moments of distribution：分布的矩函数；conditional distribution (means)：条件分布（均值）；variance：方差；standard deviation：标准差（指总体方差的平方根）；standard error：标准误差，指样本方差的平方根；skewness：偏度，度量分布的对称性；kurtosis：峰度，度量厚尾性，即度量离散程度；joint distribution：联合分布；conditional expectation：条件期望（指总体）；randomness：随机性i.i.d., independently and identically distributed：独立同分布的；sampling distribution：抽样分布，指的是当抽取不同的随机样本时，统计量的取值会有所不同，而当取遍所有的样本量为n的样本时，统计量有一个取值规律，即抽样分布，即统计量的随机性来自样本的随机性consistent (consistency)：相合的（相合性），指当样本量趋于无穷大时，估计量依概率收敛到真实值；此外，在统计的语言中，还有一个叫模型选择的相合性，指的是能依概率选取到正确的模型Central limit theory：中心极限定理；unbiased estimator：无偏估计量；uncertainty：不确定性；approximation：逼近；least squares estimator：最小二乘估计量；provisional decision：临时的决定，用于假设检验，指的是，我们现在下的结论是基于现在的数据的，如果数据变化，我们的结论可能会发生变化significance level：显著性水平，一般取0.05或者0.01,0.1，是一个预先给定的数值，指的是在原假设成立的假设下，我们可能犯的错误的概率，即拒绝原假设的概率；p-value：p-值，指的是观测到比现在观测到的统计量更极端的概率，一般p-值很小的时候要拒绝原假设，因为这说明要观测到比现在观测到的统计量更极端的情况的概率很小，进而说明现在的统计量很极端。

功夫计量阅读笔记我分享关于安神这本新书的笔记，其原因在于这本书并不特别值得一读。

这本书的定位十分尴尬，鸡肋是对其最好的描述。

Mostly Harmless Econometrics (MHE)的读者会觉得它太简单，而Freakonomics的读者则会觉得它太难。

尽管用《功夫熊猫》和上古电视剧《功夫》包装了一下，但是显然A&P的文笔跟Levitt&Dubner相比，差距不可以道里计。

所以如果没看过MHE，拿这本书作为计量功夫秘籍，很可能会觉得语焉不详，越看心儿越乱；而如果已经看过MHE，那么再花时间来看这本书，就物不所值了。

所以考虑到有些朋友可能还没来得及（或者不准备）看这本书，我贴出自己的读书笔记，聊供参考，或许能抵消一点我过去一年犯下的业障。

需要说明的是，本笔记具有私人性质，只是要点的罗列，详略安排未见得满足不同读者需求；此外，错误之处难免，恳请好心告知。

本书正文部分共分六章，其中前五章分别介绍随机试验、回归、工具变量、断点回归、双重差分，所谓功夫计量的“盖世五侠”，第六章是对以上方法的综合应用。

每一章都结合一个或数个实证案例来讲解，章节末尾有功夫大师介绍版块和附录版块。

第一章：随机试验本章案例是医疗保险实验 (RAND Health Insurance Experiment, Oregon health insurance experiment)，结论是医疗保险覆盖使得医疗服务使用率上升，但并未明显改善健康水平。

本章有一句话是我读完全书感觉最有用的，抄录在这里：“Many lifestyle choices, such as low-fat diets and vitamins, have been shown to be unrelated to health outcomes when evaluated with random assignment.” 大师版块介绍发明RCT、ANOVA、MLE等等的远古大神R A Fisher。

stata倾向得分匹配法英文回答：Propensity score matching (PSM) is a statistical technique used to estimate the causal effect of a treatment or intervention. PSM is based on the assumption that, conditional on a set of observed covariates, treatment assignment is random. This assumption is known as the conditional independence assumption (CIA).The CIA can be tested using a variety of methods, including the Rosenbaum-Rubin test and the covariate balance test. If the CIA is satisfied, then PSM can be used to estimate the average treatment effect (ATE).To estimate the ATE, PSM first estimates the propensity score for each individual. The propensity score is the probability of receiving the treatment, conditional on the observed covariates. Once the propensity scores have been estimated, PSM matches treated individuals to untreatedindividuals who have similar propensity scores.Matching can be done using a variety of methods, including nearest neighbor matching, caliper matching, and kernel matching. After matching, the ATE can be estimated by comparing the outcomes of the treated and untreated individuals.PSM is a powerful tool for estimating the causal effect of a treatment or intervention. However, it is important to note that PSM is only valid if the CIA is satisfied. If the CIA is not satisfied, then PSM may produce biased estimates of the ATE.中文回答：倾向得分匹配法（PSM）是一种统计技术，用于估计治疗或干预的因果效应。

计量经济学英汉术语名词对照及解释A校正R2（Adjusted R-Squared）：多元回归分析中拟合优度的量度，在估计误差的方差时对添加的解释变量用一个自由度来调整。

对立假设（Alternative Hypothesis）：检验虚拟假设时的相对假设。

AR（1）序列相关（AR(1) Serial Correlation）：时间序列回归模型中的误差遵循AR（1）模型。

渐近置信区间（Asymptotic Confidence Interval）：大样本容量下近似成立的置信区间。

渐近正态性（Asymptotic Normality）：适当正态化后样本分布收敛到标准正态分布的估计量。

渐近性质（Asymptotic Properties）：当样本容量无限增长时适用的估计量和检验统计量性质。

渐近标准误（Asymptotic Standard Error）：大样本下生效的标准误。

渐近t 统计量（Asymptotic t Statistic）：大样本下近似服从标准正态分布的t统计量。

渐近方差（Asymptotic Variance）：为了获得渐近标准正态分布，我们必须用以除估计量的平方值。

渐近有效（Asymptotically Effcient）：对于服从渐近正态分布的一致性估计量，有最小渐近方差的估计量。

渐近不相关（Asymptotically Uncorrelated）：时间序列过程中，随着两个时点上的随机变量的时间间隔增加，它们之间的相关趋于零。

衰减偏误（Attenuation Bias）：总是朝向零的估计量偏误，因而有衰减偏误的估计量的期望值小于参数的绝对值。

自回归条件异方差性（Autoregressive Conditional Heteroskedasticity, ARCH）：动态异方差性模型，即给定过去信息，误差项的方差线性依赖于过去的误差的平方。

一阶自回归过程[AR（1）]（Autoregressive Process of Order One [AR(1)]）：一个时间序列模型，其当前值线性依赖于最近的值加上一个无法预测的扰动。

724 心理学报 46 卷杂 , 模型中既包括结构方程 , 也包括测量方程 , 因此 , 模型的拟合检验变得很重要 (温忠麟等 , 2012。

无论是显变量还是潜变量 , 都可以利用结构方程建模 , 使用的模型可能比用显变量建立回归模型少 , 如方程 (2和 (3用一个模型就可以了 , 图 4 是其相应的路径图。

本文讨论的有调节的中介模型只涉及一个调节变量 , 如果前半路径和后半路径的调节变量不同, 分别是 U 和 V, 则图 4 和图 7 的中介效应变成 (a1+ 本文 a3U(b1+b2V, 本文提出的检验流程仍然适用。

讨论的模型只涉及一个中介变量 , 更复杂的模型包括有调节的多重中介分析 (Hayes, 2013、多水平数这些复杂据的有调节的中介分析 (刘东等 , 2012等。

模型的检验方法和步骤 , 有待进一步研究。

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[ 叶宝娟 , 温忠麟 . (2013. 有中介的调节模型检验方法 : 甄别和整合 . 心理学报 ,45, 1050–1060.] Ye, B., Yang, Q., & Hu, Z. (2012. The effect mechanism of parental control, deviant peers and sensation seeking on drug Use among reform school students. Psychological Development and Education, 28, 641–650. 不良同伴和感觉 [叶宝娟 , 杨强 , 胡竹菁 . (2012. 父母控制、寻求对工读生毒品使用的影响机制 , 心理发展与教育 , 28, 641–650.] Ye, B., Yang, Q., & Hu, Z. (2013. Effect of gratitude on adolescents’ academic achievement: Moderated mediating effect.Psychological Development and Education, 29, 192–199. [叶宝娟 , 杨强 , 胡竹菁 . (2013.感恩对青少年学业成就的影响：有调节的中介效应 , 心理发展与教育 , 29, 192–199.] Yuan, Y., & MacKinnon, D. P. (2009. Bayesian mediation analysis. Psychological Methods, 14, 301–322.5期温忠麟等: 有调节的中介模型检验方法：竞争还是替补 725 附录 1 1.0000.262 0.181 –0.019 –0.048 变量间的协方差矩阵文件 (p1.txt 1.000 0.539 0.036 0.0441.000 1.000 1.073 0.608 1.142 0.034 0.082 –0.044 0.036 ANALYSIS: Bootstrap=2000; ! Bootstrap 法抽样 2000 次 MODEL: W on X (a1 U UX (a3; !做 W 对 X,U, UX 的回归 !X 和 UX 的回归系数分别命名为 a1 和 a3 Y on X U W (b1 UW (b2; !做 Y 对 X,U, W, UW 的回归 !W 和 UW 的回归系数分别命名为 b1 和 b2 MODEL CONSTRAINT: new (H1-H7; H1= a1*b2; H2= a3*b1; H3= a3*b2; H4=a1*b1; ! a1b2 的估计 ! a3b1 的估计 ! a3b2 的估计 !当 U 等于 0 时的 (a1+a3U(b1+b2U !的中介效应的值 H5=H4＋H1＋ H2＋ H3; !当 U 等于 1 时的中介效应 (a1+a3U(b1+b2U的值 H6=H4-H1-H2＋H3; !当 U 等于 -1 时的中介效应 (a1+a3U(b1+b2U的值 H7=H5-H4; ! U 等于 1 和 0时的 (a1+a3U(b1+b2U之差 OUTPUT: cinterval (bcbootstrap; !输出系数乘积及中介效应之差的偏差校正的百分位 !Bootstrap 计算的中介效应置信区间–0.183 –0.153 –0.180 注释：变量依次为学业成就 (Y 、复原力 (W 、感恩 (X 、感恩与生活事件交互项 (UX及复原力与生生活事件 (U、活事件交互项 (UW。

causal lm公式
因果推理模型（Causal Linear Model，CLM）是一个统计模型，用于估计因果效应，即处理或干预对结果的影响。

这种模型通常用于估计处理变量对结果变量的因果效应，而不仅仅是观察到的相关性。

CLM的一般形式如下：
\(Y = \beta_0 + \beta_1X + \beta_2W + \epsilon\)
其中：
\(Y\) 是结果变量
\(X\) 是处理或干预变量
\(W\) 是潜在的混淆变量或协变量
\(\beta_0, \beta_1, \beta_2\) 是模型参数
\(\epsilon\) 是误差项
在因果推理中，我们通常对处理变量 \(X\) 的因果效应感兴趣，即
\(\beta_1\)。

这个参数可以解释为处理变量 \(X\) 变化一个单位时，结果变量 \(Y\) 的预期变化。

要估计 \(\beta_1\) 的值，通常需要使用一些因果推理的方法，例如基于反
事实的框架、结构方程模型、工具变量法或基于贝叶斯的方法等。

这些方法可以帮助我们处理观察数据中的潜在混淆因素，并估计处理变量的因果效应。

g-formulaace公式
G-formula是一种因果推断方法，用于估计在干预处理下某个特定情况的期望值。

在公式中，ACE代表平均因果效应（Average Causal Effect），而G代表加权平均因果效应（Generalized Estimating Equation）。

G-formula的公式如下：
ACE = E(Y(a=1)) - E(Y(a=0))
其中，Y代表结果变量，a代表干预变量，E代表期望值。

G-formula的计算步骤如下：
1. 使用观察到的数据建立一个预测模型，以估计在干预处理下的结果变量的期望值。

2. 使用预测模型来预测在干预处理下的结果变量的期望值，将干预变量设置为干预处理和未干预处理的值。

3. 计算干预处理和未干预处理情况下的结果变量的期望值的差异，即平均因果效应。

G-formula方法可以用于估计不同干预处理下的平均因果效应，而不需要进行随机分配。

它适用于观察研究和随机对照试验。