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Incorporating Survey Weights into Binary and Multinomial Logistic Regression Models
2015
Science Journal of Applied Mathematics and Statistics
Since sampling weights are not simply equal to the reciprocal of selection probabilities its always challenging to incorporate survey weights into likelihood-based analysis. These weights are always adjusted for various characteristics. In cases where logistic regression model is used to predict categorical outcomes with survey data, the sampling weights should be considered if the sampling design does not give each individual an equal chance of being selected in the sample. The weights are
doi:10.11648/j.sjams.20150306.13
fatcat:rcbnagctavbhtn7523ctcvxfsa