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Somers' D and Kendall's tau-a are parameters behind rank or nonparametric statistics, interpreted as differences between proportions. Given two bivariate data pairs (X1, Y1) and (X2, Y2), Kendall’s tau-a parameter tau-XY is the difference between the probability that the two X–Y pairs are...
Persistent link: https://www.econbiz.de/10005074240
Students of racial and gender inequalities are often interested in knowing to what extent an observed group difference can be attributed to differences in returns to productive abilities (discrimination effect) or to differences in the average of productive abilities (endowment effect). The...
Persistent link: https://www.econbiz.de/10005074241
Data used in applied econometrics are typically nonexperimental in nature. This makes the assumption of exogeneity of regressors untenable and poses a serious identification issue in the estimation of economic structural relationships. As far as the source of endogeneity is confined to...
Persistent link: https://www.econbiz.de/10005074242
Most survival data are analyzed by using the Cox proportional hazards model (in Stata: the stcox command). Almost by definition, a proportion of the observations will be right-censored. Analysis of covariate effects in the Cox model is couched in terms of (log) hazard ratios, and the...
Persistent link: https://www.econbiz.de/10005074243
This paper describes a natural interaction between Stata and markup languages. Stata’s programming and analysis features, together with the flexibility in output formatting of markup languages, allow generation and/or update of whole documents (reports, presentations on screen or web, etc.)....
Persistent link: https://www.econbiz.de/10005102772
If you find yourself repeatedly specifying the same options on graph commands, you should write a graphics scheme. A scheme is nothing more than a file containing a set of rules specifying how you want your graphs to look. From the size of fonts used in titles and the color of lines and markers...
Persistent link: https://www.econbiz.de/10005053301
This short talk introduces and illustrates svylorenz, a Stata 9 program for computing variance estimates for quantile group shares of total varname, cumulative quantile group shares (i.e., Lorenz curve ordinates), and the Gini coefficient. The program implements the linearization methods...
Persistent link: https://www.econbiz.de/10005053302
Controversy exists regarding proper methods for the selection of variables in confounder control in epidemiological studies. Various approaches have been proposed for selecting a subset of confounders among many possible subsets. This paper describes the use of two practical tools, Stata...
Persistent link: https://www.econbiz.de/10005053303
In teaching logistic regression for case–control studies, I ask master’s students in epidemiology to assess an interaction between a 2-level exposure and a 4-level exposure using a likelihood-ratio test. Theory suggests that the test statistic has 3 degrees of freedom, but Stata uses 2...
Persistent link: https://www.econbiz.de/10005053304
This talk discusses estimation, inference, and interpretation of panel-data models using Stata. The talk usually covers the linear RE and FE models, linear RE and FE models with AR(1) errors, linear RE and FE models with general within-panel correlation structures, Hausman–Taylor estimation,...
Persistent link: https://www.econbiz.de/10005053305