CONFIDENCE INTERVALS FOR THE COEFFICIENT OF VARIATION

The coefficient of variation (CV), defined as the ratio of the standard deviation to the mean, is often used in experimental situations. The exact distribution of the sample CV from a normally distributed population is complicated and obtaining a confidence interval for the population CV in this situation would require using the non-central t distribution and sequential techniques (Koopmans, et al., 1964). This paper explores the use of approximate distributions in determining confidence limits for the CV. The gamma distribution is used to model data appropriate for the calculation of the CV. A Monte Carlo simulation is performed to evaluate the effectiveness of four different intervals developed in this paper. A data set from a forestry experiment is analyzed using one of these techniques

Performing Two-Way Analysis of Variance Under Variance Heterogeneity

Small sample properties of the method proposed by Brunner et al. (1997) for performing two-way analysis of variance are compared to those of the normal based ANOVA method for factorial arrangements. Different effect sizes, sample sizes, and error structures are utilized in a simulation study to compare type I error rates and power of the two methods. An SAS program is also presented to assist those wishing to implement the Brunner method to real data

USING RANKS TO PERFORM EXACT AND ESTIMATED EXACT TESTS IN DESIGNED EXPERIMENTS

A procedure is studied that uses rank transformed data to perform exact and estimated exact tests which is an alternative to the commonly used F-ratio test procedure. First, a common parametric test statistic is computed using rank transformed data, where two methods of ranking - ranks taken of the original observations, and ranks taken after aligning the observations - are studied. Significance is then determined using either the exact permutation distribution of the statistic or an estimate of this distribution based on a random sample of all possible permutations. Simulation studies compare the performance of this method to both the normal theory parametric F-test and the traditional rank transform procedure. Power and nominal type-I error rates are compared under conditions when normal theory assumptions are satisfied as well as when these assumptions are violated. The method is studied for a two factor factorial arrangement of treatments in a completely randomized design and also for a split-unit experiment

JMASM8: Using SAS To Perform Two-Way Analysis Of Variance Under Variance Heterogeneity

We present SAS code to implement the method proposed by Brunner et al. (1997) for performing two-way analysis of variance under variance heterogeneity

MODELLING THE COEFFICIENT OF VARIATION IN FACTORIAL EXPERIMENTS

The coefficient of variation (CV) has long been used as a measure of the relative consistency of sample data. However, little attention has been paid to using the CV to make conclusions about the relative consistency of the population(s) from which the data are drawn, particularly when the data are observed in the context of a designed factorial experiment. This research focused on using three approximations to the exact distribution of the sample CV of normally distributed data (McKay\u27s, David\u27s, and Iglewicz and Myers\u27) in the context of the generalized linear model to develop a method for detecting main effects and interactions among factors when the population characteristic of interest is the CV

Overlapping confidence intervals or standard error intervals: What do they mean in terms of statistical significance?

We investigate the procedure of checking for overlap between confidence intervals or standard error intervals to draw conclusions regarding hypotheses about differences between population parameters. Mathematical expressions and algebraic manipulations are given, and computer simulations are performed to assess the usefulness of confidence and standard error intervals in this manner. We make recommendations for their use in situations in which standard tests of hypotheses do not exist. An example is given that tests this methodology for comparing effective dose levels in independent probit regressions, an application that is also pertinent to derivations of LC(50)s for insect pathogens and of detectability half-lives for prey proteins or DNA sequences in predator gut analysis

A Permutation Test for Compound Symmetry with Application to Gene Expression Data

The development and application of a permutation test for compound symmetry is described. In a simulation study the permutation test appears to be a level-α test and is robust to non-normality. However, it exhibits poor power, particularly for small samples

Susceptibility of stored-product psocids to aerosol insecticides

The efficacies of commercial methoprene and esfenvalerate aerosols for control of stored-product psocid pests were evaluated in simulated field studies. The efficacies of methoprene, esfenvalerate EC, the carrier Isopar-M™, and a combination of methoprene and esfenvalerate aerosols for control of Liposcelis decolor (Pearman) (Psocoptera: Liposcelididae) and Liposcelis entomophila (Enderlein) nymphs were assessed, and the effects of direct and indirect exposure of Liposcelis bostrychophila Badonnel, L. decolor, and Liposcelis paeta Pearman adults to esfenvalerate EC aerosol were evaluated. The greatest nymphal mortality attained was 76%, indicating that the four aerosols tested were ineffective against L. decolor and L. entomophila nymphs. In the direct and indirect exposure studies, the greatest adult mortalities attained for the three psocid species were 62 and 32%, respectively. Based on these data, esfenvalerate aerosol is ineffective for control of L. bostrychophila, L. decolor, L. entomophila, and L. paeta psocid species. This study shows that methoprene, esfenvalerate EC, and a combination of methoprene and esfenvalerate aerosols were ineffective against the four psocid species tested when applied at rates that are usually effective against other stored-product insect pests

Identification of transcriptional regulatory networks specific to pilocytic astrocytoma.

BackgroundPilocytic Astrocytomas (PAs) are common low-grade central nervous system malignancies for which few recurrent and specific genetic alterations have been identified. In an effort to better understand the molecular biology underlying the pathogenesis of these pediatric brain tumors, we performed higher-order transcriptional network analysis of a large gene expression dataset to identify gene regulatory pathways that are specific to this tumor type, relative to other, more aggressive glial or histologically distinct brain tumours.MethodsRNA derived from frozen human PA tumours was subjected to microarray-based gene expression profiling, using Affymetrix U133Plus2 GeneChip microarrays. This data set was compared to similar data sets previously generated from non-malignant human brain tissue and other brain tumour types, after appropriate normalization.ResultsIn this study, we examined gene expression in 66 PA tumors compared to 15 non-malignant cortical brain tissues, and identified 792 genes that demonstrated consistent differential expression between independent sets of PA and non-malignant specimens. From this entire 792 gene set, we used the previously described PAP tool to assemble a core transcriptional regulatory network composed of 6 transcription factor genes (TFs) and 24 target genes, for a total of 55 interactions. A similar analysis of oligodendroglioma and glioblastoma multiforme (GBM) gene expression data sets identified distinct, but overlapping, networks. Most importantly, comparison of each of the brain tumor type-specific networks revealed a network unique to PA that included repressed expression of ONECUT2, a gene frequently methylated in other tumor types, and 13 other uniquely predicted TF-gene interactions.ConclusionsThese results suggest specific transcriptional pathways that may operate to create the unique molecular phenotype of PA and thus opportunities for corresponding targeted therapeutic intervention. Moreover, this study also demonstrates how integration of gene expression data with TF-gene and TF-TF interaction data is a powerful approach to generating testable hypotheses to better understand cell-type specific genetic programs relevant to cancer

Potato virus X TGBp1 induces plasmodesmata gating and moves between cells in several host species whereas CP moves only in N. benthamiana leaves

AbstractExperiments were conducted to compare the plasmodesmal transport activities of Potato virus X (PVX) TGBp1 and coat protein (CP) in several plant species. Microinjection experiments indicated that TGBp1 gates plasmodesmata in Nicotiana tabacum leaves. These results support previous microinjection studies indicating that TGBp1 gates plasmodesmata in Nicotiana benthamiana and Nicotiana clevelandii leaves. To study protein movement, plasmids expressing the green fluorescent protein (GFP) gene fused to the PVX TGBp1 or CP genes were biolistically bombarded to leaves taken from four different PVX host species. GFP/TGBp1 moved between adjacent cells in N. tabacum, N. clevelandii, N. benthamiana, and Lycopersicon esculentum, whereas GFP/CP moved only in N. benthamiana leaves. Mutations m12 and m13 were introduced into the TGBp1 gene and both mutations eliminated TGBp1 ATPase active site motifs, inhibited PVX movement, reduced GFP/TGBp1 cell-to-cell movement in N. benthamiana leaves, and eliminated GFP/TGBp1 movement in N. tabacum, N. clevelandii, and L. esculentum leaves. GFP/TGBp1m13 formed aggregates in tobacco cells. The ability of GFP/CP and mutant GFP/TGBp1 fusion proteins to move in N. benthamiana and not in the other PVX host species suggests that N. benthamiana plants have a unique ability to promote protein intercellular movement