PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Analysis of Variance”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10Linked to original sources
PubMed2002

Analysis of variance frameworks in clinical child and adolescent psychology: advanced issues and recommendations.

Explores more advanced issues that researchers need to consider when using analysis of variance frameworks, building on basic issues for analysis of variance discussed in Jaccard and Guilamo-Ramos (2002). These include (a) using confidence intervals, (b) asserting group equivalence after a nonsignificant result, (c) use of magnitude estimation approaches, (d) sample size and power considerations, (e) outlier analysis, (f) violations of assumptions, and (g) missing data. Suggestions are offered for analytic practices in each of these domains.

Adolescent↗
PubMed2005

Inequality constrained analysis of variance: a Bayesian approach.

Researchers often have one or more theories or expectations with respect to the outcome of their empirical research. When researchers talk about the expected relations between variables if a certain theory is correct, their statements are often in terms of one or more parameters expected to be larger or smaller than one or more other parameters. Stated otherwise, their statements are often formulated using inequality constraints. In this article, a Bayesian approach to evaluate analysis of variance or analysis of covariance models with inequality constraints on the (adjusted) means is presented. This evaluation contains two issues: estimation of the parameters given the restrictions using the Gibbs sampler and model selection using Bayes factors in the case of competing theories. The article concludes with two illustrations: a one-way analysis of covariance and an analysis of a three-way table of ordered means.

Analysis of Variance↗
PubMed2004

Atomic mean-square displacements in proteins by molecular dynamics: a case for analysis of variance.

Information on protein internal motions is usually obtained through the analysis of atomic mean-square displacements, which are a measure of variability of the atomic positions distribution functions. We report a statistical approach to analyze molecular dynamics data on these displacements that is based on probability distribution functions. Using a technique inspired by the analysis of variance, we compute unbiased, reliable mean-square displacements of the atoms and analyze them statistically. We applied this procedure to characterize protein thermostability by comparing the results for a thermophilic enzyme and a mesophilic homolog. In agreement with previous experimental observations, our analysis suggests that the proteins surface regions can play a role in the different thermal behavior.

Algorithms↗
PubMed1993

A multiparametric data analysis showing the potential of localized proton MR spectroscopy of the brain in the metabolic characterization of neurological diseases.

We conducted an extended clinical evaluation of localized proton magnetic resonance spectroscopy (MRS) of the brain, performed on various brain diseases using short stimulated echo times. Pathologies studied were mainly multiple sclerosis, stroke, leukoaraiosis, AIDS-related leukoencephalopathies and glial tumors. Other miscellaneous pathologies were also studied. Magnetic resonance examination of the brain was conducted on a Siemens Magnetom SP63 (equipped with a 1.5 T magnet). Localized proton MRS was performed on a routine basis immediately after imaging, using the STEAM (stimulated echo acquisition mode) with a short echo time (20 ms) combined with a CHESS (chemical shift selective excitation) sequence. One or two VOI (8 ml) were examined. Data on 125 spectra were processed by principal component analysis (PCA) and conventional variance analysis. The following metabolite resonances were studied: inositol-glycine, taurine-scyllo-inositol, choline derivatives, phosphocreatine-creatine, aspartate, glutamine glutamate, N-acetylaspartate, acetate and lactate. PCA demonstrates that the different metabolic variables are independent. The analysis of groups of spectra clearly demonstrates that the metabolic profiles detected by localized MRS in various pathologies (i) differ significantly from controls, and (ii) allow a metabolic discrimination between groups of pathologies. Results of PCA are confirmed by variance analysis. Strokes are characterized by an increase in lactate concentration and leukoaraiosis by a decrease in inositol-glycine resonance. AIDS-related leukodystrophies are characterized by increases in lactate and choline concentrations. Reduction in N-acetylaspartate which is observed in most pathologies is not significant in the small lesions of white matter. Lactate has often been found in MS plaques, but no variation in the choline/phosphocreatine ratio was observed. GABA was tentatively assigned in the spectrum of a patient with epilepsy under sodium valproate treatment. This study illustrates the clinical feasibility of the technique, the value of a multiparametric data analysis in the definition of the pertinent variables characterizing the metabolic impairment, and the impact of localized proton MR spectroscopy of the brain in the assessment of cerebral suffering.

AIDS Dementia Complex↗
PubMed1981

Separating age, cohort, and time of measurement: analysis of variance or multiple regression.

This paper empirically compares the relative advantages of analysis of variance (ANOVA) and multiple regression (MR) approaches to the separation of age, cohort, and time of measurement effects in sequential research designs. The comparison utilizes four synthetic data sets, designed to have specific characteristics. The results support Adam's recent claim that standard ANOVA procedures, as described by Schaie, do not permit the development of accurate decision rules for age-period-cohort analysis. A modified dummy variable regression procedure developed by Mason, et al. is demonstrated to permit accurate attribution of variance among age, cohort, and time of measurement effects in the developmental model.

Age Factors↗
PubMed1984

A pocket calculator program for Duncan's New Multiple Range Test and analysis of variance.

A program for the TI-59 calculator to be used in analysis of variance and testing of significance of differences between each mean and every other mean by Duncan's New Multiple Range Test is presented. The test is both simple and powerful for data involving more than two treatment groups in a completely random design. Up to six groups with any number of replicates may be analyzed with this program.

Analysis of Variance↗
PubMed1986

Symmetric differences squared and analysis of variance procedures for estimating genetic and environmental variances and covariances for beef cattle weaning weight: I. Comparison via simulation.

Analysis of variance (ANOVA) and symmetric differences squared (SDS) methods for estimating genetic and environmental variances and covariances associated with beef cattle weaning weight were compared via simulation. Simulation was based on the pedigree and record structure of 503 beef weaning weights collected over 19 yr from a university herd. The SDS methodology was used with four models. The simplest model included direct (g) and maternal (gm) additive genetic effects, genetic covariance between direct and maternal additive genetic effects (sigma ggm), permanent maternal environmental effects (m) and temporary environmental effects (e). The second model also allowed for a nonzero environmental covariance (sigma mem) between dam and offspring weaning weights. Models 3 and 4 were models 1 and 2, respectively, expanded to include a grandmaternal genetic effect (gn) and covariances sigma ggn and sigma gmgn. Two ANOVA solution sets for the parameters of model 4 were obtained using sire, dam, maternal grandsire, maternal grandam and phenotypic variances and offspring-dam (covOD), offspring-sire (covOS), offspring-grandam (covOGD), and offspring-maternal half-aunt or uncle (covOMH) covariances. Four ANOVA solution sets for the parameters of model 2 were obtained using sire, dam, within dam and maternal grandsire variances, covOD and either covOS or covOGD. Two sets of 1,000 replicates of the data were simulated. These data were used to compare precision and accuracy of SDS and ANOVA estimators, to estimate correlations among SDS and ANOVA estimators, and to study the importance of taking inbreeding into account with SDS methodology. All ANOVA estimators for rho ggm were biased downward. The SDS procedure had a clear advantage over ANOVA. Averages of SDS estimates were closer to parameter values used to simulate the data and their standard deviations were generally smaller. The standard deviations of both SDS and ANOVA estimates of rho ggm were very large. It is important to allow for a nonzero sigma mem (at least when it is negative) when using SDS methods; otherwise estimators of sigma 2gm and sigma ggm are biased upward and downward, respectively.

Analysis of Variance↗