Index Catalog // ScholarsArchive@OSU

Estimating root mean squared error in the one-way random model

Creator:: Siripanich, Pachitjanut (Dasnanjali)
Resource Type:: Dissertation
Full Text:: One-way Random Model Abstract approved: Redacted for privacy David S. Birkes Consider a one-way

Testing for location after transformation to normality

Creator:: Halawa, Adel Mahmoud
Abstract:: In the problem of testing the median using a random sample from a certain distribution, and if no other parametric family is suggested, the t-test is known to be the optimal procedure when this distribution is normal. If the sample appears to be non-normal, one has the choice either to...
Resource Type:: Dissertation
Full Text:: approved: Redacted for Privacy David S. Birkes In the problem of testing the median using a random sample

F-tests in partially balanced and unbalanced mixed linear models

Creator:: Utlaut, Theresa L.
Abstract:: This dissertation considers two approaches for testing hypotheses in unbalanced mixed linear models. The first approach is to construct a design with some type of structure or "partial" balance, so that some of the optimal properties of a completely balanced design hold. It is shown that for a particular type...
Resource Type:: Dissertation
Full Text:: Balanced and Unbalanced Mixed Linear Models Abstract approved: David S. Birkes This dissertation

Explicit linear maximum likelihood estimation in mixed models

Creator:: Wulff, Shaun S.
Abstract:: Mixed models have been widely used to model data from experiments which have fixed and random factors. Often there is interest in the estimation of fixed effects and variance components. The likelihood procedure is a general technique that has been applied to such problems. This procedure can be computationally difficult,...
Resource Type:: Dissertation
Full Text:: approved: David S. Birkes Mixed models have been widely used to model data from experiments which have

Confidence intervals and tests for variance-component ratios in mixed linear models

Creator:: Li, Yulan
Resource Type:: Dissertation
Full Text:: -Component Ratios in Mixed Linear Models Abstract approved: David R. Thomas/David S. Birkes Mixed linear

Unconditional estimating equation approaches for missing data

Creator:: Lu, Lin
Abstract:: Missing data can lead to biased and inefficient estimation if the missing mechanism is not taken into account in the analysis. In this dissertation we propose two estimators that, under fairly general conditions, are asymptotically unbiased. The first proposed estimator assume the data are missing at random (MAR) and does...
Resource Type:: Dissertation
Full Text:: for Missing Data. Abstract approved: Annie Qu David S. Birkes Missing data can lead to biased and

Kenward-Roger approximate F test for fixed effects in mixed linear models

Creator:: Alnosaier, Waseem S.
Abstract:: For data following a balanced mixed Anova model, the standard Anova method typically leads to exact F tests of the usual hypotheses about fixed effects. However, for most unbalanced designs with most hypotheses, the Anova method does not produce exact tests, and approximate methods are needed. One approach to approximate...
Resource Type:: Dissertation
Full Text:: Effects in Mixed Linear Models. Abstract approved: David S. Birkes

Admissibility in linear models

Creator:: Azzam, Abdul-Mordy Hamed
Resource Type:: Dissertation
Full Text:: 30, 1980 Title: ADMISSIBILITY IN LINEAR MODELS Redacted for privacy Abstract approved: David S

Completeness and sufficiency under normality in mixed model designs

Creator:: VanLeeuwen, Dawn
Resource Type:: Dissertation
Full Text:: the crystal because the volume of a reciprocal lattice primitive cell is (21) , where v = V i s the

Statistical aspects of two measurement problems : defining taxonomic richness and testing with unanchored responses

Creator:: Ritter, Kerry
Abstract:: Statisticians often focus on sampling or experimental design and data analysis while paying less attention to how the response is measured. However, the ideas of statistics may be applied to measurement problems with fruitful results. By examining the errors of measured responses, we may gain insight into the limitations of...
Resource Type:: Dissertation
Full Text:: approved: N S ttU uhart David Birkes Statisticians often focus on sampling or experimental design and

ScholarsArchive@OSU

Estimating root mean squared error in the one-way random model

Testing for location after transformation to normality

F-tests in partially balanced and unbalanced mixed linear models

Explicit linear maximum likelihood estimation in mixed models

Confidence intervals and tests for variance-component ratios in mixed linear models

Unconditional estimating equation approaches for missing data

Kenward-Roger approximate F test for fixed effects in mixed linear models

Admissibility in linear models

Completeness and sufficiency under normality in mixed model designs

Statistical aspects of two measurement problems : defining taxonomic richness and testing with unanchored responses

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