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Full-Text Articles in Statistics and Probability
New Technique For Imputing Missing Item Responses For An Ordinal Variable: Using Tennessee Youth Risk Behavior Survey As An Example., Andaleeb Abrar Ahmed
New Technique For Imputing Missing Item Responses For An Ordinal Variable: Using Tennessee Youth Risk Behavior Survey As An Example., Andaleeb Abrar Ahmed
Electronic Theses and Dissertations
Surveys ordinarily ask questions in an ordinal scale and often result in missing data. We suggest a regression based technique for imputing missing ordinal data. Multilevel cumulative logit model was used with an assumption that observed responses of certain key variables can serve as covariate in predicting missing item responses of an ordinal variable. Individual predicted probabilities at each response level were obtained. Average individual predicted probabilities for each response level were used to randomly impute the missing responses using a uniform distribution. Finally, likelihood ratio chi square statistics was used to compare the imputed and observed distributions. Two other …
A Statistical Evaluation Of Algorithms For Independently Seeding Pseudo-Random Number Generators Of Type Multiplicative Congruential (Lehmer-Class)., Robert Grisham Stewart
A Statistical Evaluation Of Algorithms For Independently Seeding Pseudo-Random Number Generators Of Type Multiplicative Congruential (Lehmer-Class)., Robert Grisham Stewart
Electronic Theses and Dissertations
To be effective, a linear congruential random number generator (LCG) should produce values that are (a) uniformly distributed on the unit interval (0,1) excluding endpoints and (b) substantially free of serial correlation. It has been found that many statistical methods produce inflated Type I error rates for correlated observations. Theoretically, independently seeding an LCG under the following conditions attenuates serial correlation: (a) simple random sampling of seeds, (b) non-replicate streams, (c) non-overlapping streams, and (d) non-adjoining streams. Accordingly, 4 algorithms (each satisfying at least 1 condition) were developed: (a) zero-leap, (b) fixed-leap, (c) scaled random-leap, and (d) unscaled random-leap. Note …