Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...
This paper studies a model widely used in the weak instruments literature and establishes admissibility of the weighted average power likelihood ratio tests recently derived by Andrews, Moreira, and ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between ...
Quantification of the dependence of the odds ratio on concomitant variables associated with each of several 2 x 2 tables, using a regression model proposed by Zelen [1971], is an important tool for ...
This is the third in a series of lecture notes which, if tied together into a textbook, might be entitled “Practical Regression.” The purpose of the notes is to supplement the theoretical content of ...
Many complex disease traits are observed to be associated with single nucleotide polymorphism (SNP) interactions. In testing small-scale SNP–SNP interactions, variable selection procedures in logistic ...
To use input series, list the input series in a CROSSCORR= option on the IDENTIFY statement and specify how they enter the model with an INPUT= option on the ESTIMATE statement. For example, you might ...
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