Basic Principles of Statistical Inference

Basic Principles of Statistical Inference Kosuke Imai Department of Politics Princeton University POL572 Quantitative Analysis II Spring 2016 Kosuke Imai (Princeton) Basic Principles POL572 Spring 2016 1 / 66

  Principles, Statistical, Inference, Principles of statistical inference

mediation: R Package for Causal Mediation Analysis

mediation analysis under the assumption of sequential ignorability. Many of these function-alities are described in detail inImai et al. (2010b), but the current version of the package accommodates a larger class of statistical models. The model-based causal mediation analysis proceeds in two steps. First, the researcher speci-

  Analysis, Packages, Mediation, Casual, Package for causal mediation analysis

Causal Directed Acyclic Graphs - Harvard University

Causal Directed Acyclic Graphs Kosuke Imai Harvard University STAT186/GOV2002 CAUSAL INFERENCE Fall 2019 Kosuke Imai (Harvard) Causal DAGs Stat186/Gov2002 Fall 20191/16. ... 1 Identify all paths from any vertex in A to any vertex in B 2 Check if each path isblocked 3 If all paths are blocked, then A is d-separatedfrom B by C

  Path, Graph

A General Approach to Causal Mediation Analysis

approach to the panel data settings (e.g., Cole & Maxwell, 2003; MacKinnon, 2008, Chapter 8), and multiple (e.g., MacKinnon, 2000; Preacher & Hayes, 2008) and multilevel (e.g., Krull & MacKinnon, 1999) mediators, all of which are beyond the scope of the current article. A Running Example: The Job Search Intervention Study (JOBS II)

  Study, Approach, Multilevel

POL 571: Convergence of Random Variables

model because in theory one can obtain the infinite number of random sample from the population (hence, the population size is infinite). In the social sciences, this often requires one to think about ... implies that the marginal distribution of X i is the same as the case of sampling with replacement. 1.

  Model, Marginal

POL571 Lecture Notes: Expectation and Functions of Random ...

Finally, we emphasize that the independence of random variables implies the mean independence, but the latter does not necessarily imply the former. Theorem 2 (Expectation and Independence) Let X and Y be independent random variables. Then, the two random variables are mean independent, which is defined as, E(XY) = E(X)E(Y).

  Lecture, Variable, Random, Random variables

Measuring the Economic Impact of Civil War

5 Improving Estimation 13 ... Wars that spill out across the entire country, require the highest level of military recruitment, and result in the greatest number of fatalities are the most damaging to the domestic economy. This paper also makes methodological improvements. First, we improve the data.

  Civil, Spill, Estimation, Civil war

Survival Data Analysis - Harvard University

King, Alt, Burns, and Laver (1990). AJPS Censoring: 12 months prior to the end of the constitutional inter-election period Is censoring independent? Kosuke Imai (Princeton) Survival Data POL573 Fall 2015 8 / 39

  Survival, Jpas

Mathematical Statistics, Lecture 2 Statistical Models

Assumptions about the distribution of E over the cases (2) Specify/define a criterion for judging different estimators. (3) Characterize the best estimator and apply it to the given data. (4) Check the assumptions in (1). (5) If necessary modify model and/or assumptions and go to (1). íõ. MIT 18.655 Statistical Models

  Statistics, Statistical, Mathematical, Assumptions, Mathematical statistics

The Assumption(s) of Normality - University of Iowa

This is why these statistical procedures are called . By definition,parametricparametric stats are those that make assumptions about the shape of the sampling distribution of the value of interest (i.e., they make assumptions about the skew and kurtosis parameters, among other things; hence the name).

  Statistical, Assumptions

Chapter 440 Discriminant Analysis - Statistical Software

Discriminant analysis does not make the strong normality assumptions that MANOVA does because the emphasis is on classification. A sample size of at least twenty observ ations in the smallest group is usually adequate to ensure robustness of …

  Statistical, Assumptions

OLS in Matrix Form - Stanford University

OLS in Matrix Form 1 The True Model † Let X be an n £ k matrix where we have observations on k independent variables for n observations. Since our model will usually contain a constant term, one of the columns in the X matrix will contain only ones. This column should be treated exactly the same as any