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- Experimental design (2)
- Monte Carlo simulation (2)
- Cluster-randomized trials (1)
- Confirmatory Factor Analysis (1)
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- Education (1)
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- Intraclass correlation (1)
- Jonckheere-Terpstra (1)
- Matching (1)
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- Science education evaluation (1)
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Articles 1 - 7 of 7
Full-Text Articles in Design of Experiments and Sample Surveys
Nonparametric Tests For Replicated Latin Squares, Joseph Yang
Nonparametric Tests For Replicated Latin Squares, Joseph Yang
Dissertations
Two classes of nonparametric procedures for a replicated Latin square design that test for both general and increasing alternatives are developed. The two classes of procedures are similar in the sense that both transform the data so that existing well-known tests for randomized complete block designs can be utilized. On the other hand, the two classes differ in the way that the data is transformed - one class essentially aggregates the data while the other class aligns the data. Within these contexts, the exact distributions and asymptotic distributions are discussed, when applicable. The exact distributions are easily computed using the …
Some Nonparametric Ordered Restricted Inference Problems In The Context Of A Statistical Education Study, Bradford M. Dykes
Some Nonparametric Ordered Restricted Inference Problems In The Context Of A Statistical Education Study, Bradford M. Dykes
Dissertations
Over the past 10 years, the Department of Statistics at Western Michigan University has developed a question generating system that can be used for creating multiple forms of exams, quizzes and homework for online and face-to-face use. This system can also be used to provide students with a form of instantaneous feedback. With the goal of analyzing how different levels of feedback in an online learning environment impacts students' performance on assignments, this study presents data collected on two semesters of students enrolled in three different meeting types (strictly online, typical face-to-face, and honors face-to-face) of an introductory Statistics course. …
Empirical Evaluation Of Different Features Of Design In Confirmatory Factor Analysis, Deyab Almaleki
Empirical Evaluation Of Different Features Of Design In Confirmatory Factor Analysis, Deyab Almaleki
Dissertations
Factor analysis (FA) is the study of variance within a group. Within-subject variance (WSV) is affected by multiple features in a study context, such as: the study experimental design (ED) and sampling design (SD), thus anything that influences or changes variance may affect the conclusions related to FA.
The aim of this study was to provide empirical evaluation of the influence of different aspects of ED and SD on WSV in the context of FA in terms of model precision and model estimate stability. Four Monte Carlo population correlation matrices were hypothesized based on different communality magnitudes (high, moderate, low, …
Improving The Design Of Cluster-Randomized Trials In Education: Informing The Selection Of Variance Design Parameter Values For Science Achievement Studies, Carl D. Westine
Dissertations
The purpose of this three-essay dissertation is to provide practical guidance to evaluators planning cluster-randomized trials (CRTs) of science achievement. In an educational setting, interventions are often administered at the cluster level, while outcomes are typically measured at the student level through standardized achievement testing. When evaluating an intervention, a CRT is appropriate because it allows for treatment to be modeled at a different level than the unit of analysis, and properly accounts for the violation of independence that occurs due to nesting. Accurately designing a CRT involves estimating variance parameters (i.e., intraclass correlations [ICCs] and percent of variance explained …
A Comparative Study Of Exact Versus Propensity Matching Techniques Using Monte Carlo Simulation, Mukaria J. J. Itang'ata
A Comparative Study Of Exact Versus Propensity Matching Techniques Using Monte Carlo Simulation, Mukaria J. J. Itang'ata
Dissertations
Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized designs. In such situations, subject matching provides an alternative design approach for conducting causal inference studies. This study examined various design conditions hypothesized to affect matching procedures’ bias recovery ability.
See attachment for full abstract.
Empirical Spectral Analysis Of Random Number Generators, David Zeitler
Empirical Spectral Analysis Of Random Number Generators, David Zeitler
Dissertations
Computer simulation procedures have become a staple of research and development in many fields, including statistics. The generation of pseudo random number sequences is the core of computer simulation procedures. Validity of research results often depend on the underlying validity of the generator being used.
In this work we develop the machinery for a class of tests of spatial uniformity based on a multi-dimensional Fourier transform of the empirical probability density function. The test can be adapted to specific requirements and has the added advantage that it has computational complexity that is relatively independent of the number of data points …
A Comparison Of Methods For Detection Of Qualitative Interaction In Multicenter Trials, Boyd Jay Hanson
A Comparison Of Methods For Detection Of Qualitative Interaction In Multicenter Trials, Boyd Jay Hanson
Dissertations
This research evaluated and compared three methods for the detection of qualitative treatment-by-center interaction proposed by Azzalini and Cox, Gail and Simon and Ciminera et al., through the analysis of simulated data for multicenter studies of two and three centers with two treatments. The effect of unequal sample size and the presence of an overall treatment effect on characteristics of the methods were examined.
The approach, underlying assumptions and theory of the three methods differ. For this study, they were adapted to establish a common basis for evaluation, thus allowing a meaningful comparison of the methods. For the test presented …