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Full-Text Articles in Physical Sciences and Mathematics
Robust Interval Estimation Of A Treatment Effect In Observational Studies Using Propensity Score Matching, Scott F. Kosten
Robust Interval Estimation Of A Treatment Effect In Observational Studies Using Propensity Score Matching, Scott F. Kosten
Dissertations
Estimating the treatment effect between a treatment group and a control group in an observational study is a challenging problem in statistics. Without random assignment of subjects, there are likely to be differences between the treatment group and control group on a set of baseline covariates. If one of these baseline covariates is correlated to the response variable, then the difference in sample means between the groups is likely to be a biased estimate of the true treatment effect.
Propensity score matching has become an increasingly popular strategy for reducing bias in estimates of the treatment effect. This reduction in …
Confidence Intervals And Tests On The Difference Of Means Of Two Delta Distributions, Karen Grace Villarente Rosales
Confidence Intervals And Tests On The Difference Of Means Of Two Delta Distributions, Karen Grace Villarente Rosales
Dissertations
Various research fields produce data that are lognormally distributed and inflated with zero values. This type of data follows a delta distribution. In this study, we want to extensively investigate different interval and hypothesis testing methods for comparing the means of two delta populations to see which methods are optimal under different conditions of the populations.
For confidence intervals, existing MVUE methods are extended to two sample cases and compared to classical and two proposed robust methods. We investigated the performance of the classical Student's t, Welch t, and Wilcoxon-based interval to see if these methods really perform badly on …
On Robustification Of Some Procedures Used In Analysis Of Covariance, Kuanwong Watcharotone
On Robustification Of Some Procedures Used In Analysis Of Covariance, Kuanwong Watcharotone
Dissertations
This study discusses robust procedures for the analysis of covariance (ANCOVA) models. These methods are based on rank-based (R) fitting procedures, which are quite analogous to the traditional ANCOVA methods based on least squares fits. Our initial empirical results show that the validity of R procedures is similar to the least squares procedures. In terms of power, there is a small loss in efficiency to least squares methods when the random errors have a normal distribution but the rank-based procedures are much more powerful for the heavy-tailed error distributions in our study.
Rank-based analogs are also developed for pick-a-point, adjusted …