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Applied scientists, especially public health scientists, frequently want to know how much good can be caused by a proposed intervention. For instance, they might want to estimate how much we could decrease the level of a disease, in a dream scenario where the whole world stopped smoking,...
Persistent link: https://www.econbiz.de/10011132927
Factor variables are defined as categorical variables with integer values, which may represent values of some other kind, specified by a value label. We frequently want to generate such variables in Stata datasets, especially resultssets, which are output Stata datasets produced by Stata...
Persistent link: https://www.econbiz.de/10010897935
So-called non-parametric methods are in fact based on estimating and testing parameters, usually either rank parameters or spline parameters. Two comprehensive packages for estimating these are somersd (for rank parameters) and bspline (for spline parameters). Both of these estimate a wide range...
Persistent link: https://www.econbiz.de/10010928900
Medical researchers frequently make statements that one model pre- dicts survival better than another, and they are frequently challenged to provide rigorous statistical justification for those statements. Stata provides the estat concordance command to calculate the rank parameters Harrell’s...
Persistent link: https://www.econbiz.de/10008673837
I research the market efficiency of the German 6/49 parimutuel lottery game using Stata. To this end, I investigate the existence of profit opportunities for particularly unpopular combinations of numbers (Papachristou and Karamanis (1998)), employing the covariates proposed by Henze and Riedwyl...
Persistent link: https://www.econbiz.de/10004970623
A Stata program will be presented for improved quality control of econometric models. It is well known that reported econometric results often have unknown reliability because of selective reporting by the researcher. In particular, t-statistics are often uninformative or misleading when...
Persistent link: https://www.econbiz.de/10004970624
Literature on causal inference has emphasized the average causal effect, defined as the mean difference in potential outcomes under different treatment conditions. We consider marginal regression models that describe how causal effects vary in relation to covariates. To estimate parameters, we...
Persistent link: https://www.econbiz.de/10004970626
The quaids ado files written by Brian Poi provide a good template for constructing alternative ado files for maximum likelihood estimation of demand systems. I describe how I used the template to construct ado files to estimate a five commodity almost ideal demand system with demographic...
Persistent link: https://www.econbiz.de/10004970627
Following in the footsteps of the Stata user-written command ivtreatreg, recently proposed by the author (Cerulli, 2012), the paper presents a new Stata routine— contreatreg—for estimating a Dose Response Treatment Model under continuous treatment endogeneity and heterogeneous...
Persistent link: https://www.econbiz.de/10011132924
Most of the microeconometrics studies are being based on the causal inference analysis. diff provides to the researcher an easy-to-use tool to perform the difference-in-differences estimation from a two-period panel dataset designed for an impact evaluation. It combines the conditional...
Persistent link: https://www.econbiz.de/10011132925