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Full-Text Articles in Statistics and Probability
Mdc-R-Code, Joseph M. Hilbe
Mdc-R-Code, Joseph M. Hilbe
Joseph M Hilbe
Modeling Count Data: R code in book provided for use
Mcd - Stata Commands, Joseph M. Hilbe
Mcd - Stata Commands, Joseph M. Hilbe
Joseph M Hilbe
Stata commands and affiliated files for examples in book. Text file explanation of command names is included. 103 files in total
Mcd-Description, Joseph M. Hilbe
Mcd-Description, Joseph M. Hilbe
Joseph M Hilbe
Modeling Count Data - description of Data Files with examples using R, Stata and SAS
Mcd-Information-, Joseph M. Hilbe
Mcd-Information-, Joseph M. Hilbe
Joseph M Hilbe
Modeling Count Data - Information about book and resources
Mcd - 11 R Data Files From Book, Joseph M. Hilbe
Mcd - 11 R Data Files From Book, Joseph M. Hilbe
Joseph M Hilbe
Modeling Count Data: ZIP file with 11 R data files from book
Mcd - 11 Stata Data Files, Joseph M. Hilbe
Mcd - 11 Stata Data Files, Joseph M. Hilbe
Joseph M Hilbe
Modeling Count Data: 11 Stata files from book
Hilbe-Mcd-Cvs-Data, Joseph M. Hilbe
Hilbe-Mcd-Cvs-Data, Joseph M. Hilbe
Joseph M Hilbe
Modeling Count Data, data files from book in CVS format
Mcd Information, Joseph M. Hilbe
Mcd Description Data Files: Stata-R-Sas-Excel, Joseph M. Hilbe
Mcd Description Data Files: Stata-R-Sas-Excel, Joseph M. Hilbe
Joseph M Hilbe
Modeling Count Data: Description of Data Files R, Stata, SAS examples
Mcd-Figures-Code, Joseph M. Hilbe
Mcd-Figures-Code, Joseph M. Hilbe
Joseph M Hilbe
Modeling Count Data, code for Figures in book - R and Stata
Mdc-Sas-Code, Joseph M. Hilbe
Mdc-Sas-Code, Joseph M. Hilbe
Joseph M Hilbe
Modeling Count Data, SAS files for download and use
Mcd-Data-Sas, Joseph M. Hilbe
Mcd-Data-Sas, Joseph M. Hilbe
Joseph M Hilbe
Modeling Count Data, 11 SAS data files. SAS users
Interpretation And Prediction Of A Logistic Model, Joseph M. Hilbe
Interpretation And Prediction Of A Logistic Model, Joseph M. Hilbe
Joseph M Hilbe
A basic overview of how to model and interpret a logistic regression model, as well as how to obtain the predicted probability or fit of the model and calculate its confidence intervals. R code used for all examples; some Stata is provided as a contrast.
Sas Macro: Testing Marginal Homogeneity In Clustered Matched-Pair Data, Zhao Yang
Sas Macro: Testing Marginal Homogeneity In Clustered Matched-Pair Data, Zhao Yang
Zhao (Tony) Yang, Ph.D.
The SAS Macro and simulated data example are used to demonstrate the application of tests for marginal homogeneity in clustered matched-pair data.
Sas Macro: Weighted Kappa Statistic For Clustered Matched-Pair Ordinal Data, Zhao Yang
Sas Macro: Weighted Kappa Statistic For Clustered Matched-Pair Ordinal Data, Zhao Yang
Zhao (Tony) Yang, Ph.D.
This SAS macro calculate the weighted kappa statistic and its corresponding non-parametric variance estimator for the clustered matched-pair ordinal data.
Sas Macro: Kappa Statistic For Clustered Physician-Patients Polytomous Data, Zhao Yang
Sas Macro: Kappa Statistic For Clustered Physician-Patients Polytomous Data, Zhao Yang
Zhao (Tony) Yang, Ph.D.
This SAS macro calculate the kappa statistic and its semi-parametric variance estimator for the clustered physician-patients polytomous data. The proposed method depends on the assumption of conditional independence for the clustered physician-patients data structure.
On Likelihood Ratio Tests When Nuisance Parameters Are Present Only Under The Alternative, Cz Di, K-Y Liang
On Likelihood Ratio Tests When Nuisance Parameters Are Present Only Under The Alternative, Cz Di, K-Y Liang
Chongzhi Di
In parametric models, when one or more parameters disappear under the null hypothesis, the likelihood ratio test statistic does not converge to chi-square distributions. Rather, its limiting distribution is shown to be equivalent to that of the supremum of a squared Gaussian process. However, the limiting distribution is analytically intractable for most of examples, and approximation or simulation based methods must be used to calculate the p values. In this article, we investigate conditions under which the asymptotic distributions have analytically tractable forms, based on the principal component decomposition of Gaussian processes. When these conditions are not satisfied, the principal …