Tag Archives: Statistics & Econometrics

Problems with Propensity Score Matching (wonkish) .[embedded content]

Statistical inference and sampling assumptions Real probability samples have two great benefits: (i) they allow unbiased extrapolation from the sample; (ii) with data internal to the sample, it is possible to estimate how much results are likely to change if another sample is taken. These benefits, of course, have a price: drawing probability samples is hard work. An investigator who assumes that a convenience sample is like a random sample seeks to obtain...

Fisher’s exact test (student stuff) .[embedded content]

Significance testing and the real tasks of social science After having mastered all the technicalities of regression analysis and econometrics, students often feel as though they are masters of the universe. I usually cool them down with the required reading of Christopher Achen’s modern classic Interpreting and Using Regression. It usually gets​ them back on track again, and they understand that no increase in methodological sophistication … alter the...

Death penalties and homicides — a D-I-D analysis .[embedded content]

John Snow and the birth of causal inference [embedded content] If anything, Snow’s path-breaking research underlines how important it is not to equate science with statistical calculation. All science entails human judgment, and using statistical models doesn’t relieve us of that necessity. Working with misspecified models, the scientific value of statistics is actually zero — even though you’re making valid statistical inferences! Statistical models are no...

Multilevel modeling (student stuff) .[embedded content]

Model validation and significance testing In its standard form, a significance test is not the kind of ‘severe test’ that we are looking for in our search for being able to confirm or disconfirm empirical scientific hypotheses. This is problematic for many reasons, one being that there is a strong tendency to accept the null hypothesis since they can’t be rejected at the standard 5% significance level. In their standard form, significance tests bias against...

Machine learning cross-validation (student stuff) .[embedded content]

Use of covariates in RCTs (wonkish) .[embedded content]