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PubMed2007

[Analysis of variance of repeated data measured by water maze with SPSS].

OBJECTIVE: To introduce the method of analyzing repeated data measured by water maze with SPSS 11.0, and offer a reference statistical method to clinical and basic medicine researchers who take the design of repeated measures. METHODS: Using repeated measures and multivariate analysis of variance (ANOVA) process of the general linear model in SPSS and giving comparison among different groups and different measure time pairwise. RESULTS: Firstly, Mauchly's test of sphericity should be used to judge whether there were relations among the repeatedly measured data. If any (P<or=0.05), multivariate ANOVA should be taken next, or Greenhouse-Geisser corrected results should be taken. Treated effect could be evaluated by estimating between-subject variance. Repeated measurement effect or its interactive effect with treated group could be evaluated by estimating within-subject variance. The method of Bonferroni should be used to do pairwise comparisons of the repeatedly measured data in different measurement time of each treated group. With multivariate ANOVA, data in different treated group of each measurement time could be compared pairwise. CONCLUSION: The repeated measures process of the general linear model is suitable for variance analysis of repeatedly measured data. SPSS statistical package is available to fulfil this process.

Analysis of Variance↗
PubMed2004

Can low-magnification stereomicroscopy reveal diet?

A new method of scoring dental microscopic use wear, initially developed for and applied to extant and extinct ungulates, is here applied to primates, and the efficacy of the method as a tool for diagnosing diet in both ungulates and primates is established. The method employs standard refractive light microscopy instead of scanning electron microscopy (SEM), and all use-wear features are counted or scored under low magnification (35 x). We use measurement systems analysis (variance components analysis of sources of measurement error) to evaluate the consistency and reproducibility of measurements using this method. The method is shown to have low intra- and inter-observer measurement error, and to effectively distinguish among graminivores, folivores, and frugivores. It can also be used to identify seed predators and to diagnose hard-object feeding. The method is also shown to be robust to the selection of measurement site; it works equally well when applied to upper or to lower molars. Finally, we use analysis of variance to examine the consistency of the signals across mammalian orders, and discriminant function analysis to develop dietary diagnostic tools for a set of "classified" primates with known diets. We test the success of these tools not merely by examining their a posteriori classification "success," but by using them to construct predicted dietary profiles for a sample of unclassified extant primate species, again with known diets.

Analysis of Variance↗
PubMed1989

One-way analysis of variance with unequal variances.

We have designed a statistical test that eliminates the assumption of equal group variances from one-way analysis of variance. This test is preferable to the standard technique of trial-and-error transformation and can be shown to be an extension of the Behrens-Fisher T test to the case of three or more means. We suggest that this procedure be used in most applications where the one-way analysis of variance has traditionally been applied to biological data.

Analysis of Variance↗
PubMed2001

Anthropophobia: its meaning and concomitant experiences.

This study investigated the essential feature and concomitant experiences of anthropophobia, a culturally specific phobic disorder in China and Japan. One hundred and fifty subjects, including 50 anthropophobic, 50 neurasthenic and 50 normal subjects, were recruited from hospitals and downtown residential areas in Beijing. Measures of anthropophobic symptoms and DSM-III-R depressive and anxiety symptoms were administered to all subjects. Nonparametric analysis of variance, analysis of variance (ANOVA and MANOVA) and Fisher's exact test were performed to examine group differences on each symptomatic item of the three measures. Results indicate that the core anthropophobic symptoms include a fear of making eye contact with others and a fear of being watched by others, which essentially express fears of others' judgement or opinion of oneself. Anxiety and depression are associated features of anthropophobia. However, these concomitants are experienced more cognitively and less somatically in the case of anthropophobia than neurasthenia.

Adult↗
PubMed1990

Missing data in two-way analysis of variance.

We previously described a regression approach to analysis of variance computations that permitted analysis of unbalanced designs and experiments with missing data in two-way (or higher) analyses of variance Am. J. Physiol. 255 (Regulatory Integrative Comp. Physiol. 24): R353-R367, 1988. That approach can only be used correctly under a set of narrow, and relatively uninteresting, circumstances. In fact, in the example we worked, we extended that approach beyond its intended scope and incorrectly computed F statistics for testing hypotheses about the main effects of strain of rat and nephron site in a study of renal Na(+)-K(+)-adenosinetriphosphatase. This paper presents the correct approach, which can be generalized to most situations likely to be encountered when two-way, or higher, analyses of variance are used.

Adenosine Triphosphatases↗
PubMed2002

The application of analysis of variance (ANOVA) to different experimental designs in optometry.

Analysis of variance (ANOVA) is the most efficient method available for the analysis of experimental data. Analysis of variance is a method of considerable complexity and subtlety, with many different variations, each of which applies in a particular experimental context. Hence, it is possible to apply the wrong type of ANOVA to data and, therefore, to draw an erroneous conclusion from an experiment. This article reviews the types of ANOVA most likely to arise in clinical experiments in optometry including the one-way ANOVA ('fixed' and 'random effect' models), two-way ANOVA in randomised blocks, three-way ANOVA, and factorial experimental designs (including the varieties known as 'split-plot' and 'repeated measures'). For each ANOVA, the appropriate experimental design is described, a statistical model is formulated, and the advantages and limitations of each type of design discussed. In addition, the problems of non-conformity to the statistical model and determination of the number of replications are considered.

Analysis of Variance↗
PubMed2005

AnovArray: a set of SAS macros for the analysis of variance of gene expression data.

BACKGROUND: Analysis of variance is a powerful approach to identify differentially expressed genes in a complex experimental design for microarray and macroarray data. The advantage of the anova model is the possibility to evaluate multiple sources of variation in an experiment. RESULTS: AnovArray is a package implementing ANOVA for gene expression data using SAS statistical software. The originality of the package is 1) to quantify the different sources of variation on all genes together, 2) to provide a quality control of the model, 3) to propose two models for a gene's variance estimation and to perform a correction for multiple comparisons. CONCLUSION: AnovArray is freely available at http://www-mig.jouy.inra.fr/stat/AnovArray and requires only SAS statistical software.

Algorithms↗
PubMed1986

[Discussion of errors and measuring strategies in morphometry using analysis of variance].

Statistical techniques known as the analysis of variance make it possible for the morphologist to plan work in such a way as to get quantitative data with the greatest possible economy of effort. This paper explains how to decide how many measurements to make per micrograph, how many micrographs per tissue block or organ, and how many organs or individuals are necessary for getting an exactness of sufficient quality of the results. The examples furnished have been taken from measuring volume densities of mitochondria in heart muscle cells and from cell counting in lymph nodes. Finally we show, how to determine sample sizes, if we are interested in demonstration of significant differences between mean values.

Analysis of Variance↗
PubMed2001

Linkage analysis of quantitative traits in randomly ascertained pedigrees: comparison of penetrance-based and variance component analysis.

Penetrance-based linkage analysis and variance component linkage analysis are two methods that are widely used to localize genes influencing quantitative traits. Using computer programs PAP and SOLAR as representative software implementations, we have conducted an empirical comparison of both methods' power to map quantitative trait loci in extended, randomly ascertained pedigrees, using simulated data. Two-point linkage analyses were conducted on several quantitative traits of different genetic and environmental etiology using both programs, and the lod scores were compared. The two methods appear to have similar power when the underlying quantitative trait locus is diallelic, with one or the other method being slightly more powerful depending on the characteristics of the quantitative trait and the quantitative trait locus. In the case of a multiallelic quantitative trait locus, however, the variance component approach has much greater power. These findings suggest that one should give careful thought to the likely allelic architecture of the quantitative trait to be analyzed when choosing between these two analytical approaches. It may be the case in general that linkage methods which explicitly or implicitly rely on the assumption of a diallelic trait locus fare poorly when this assumption is incorrect.

Chromosome Mapping↗
PubMed1989

Sample size and statistical power in the hierarchical analysis of variance: applications in morphometry of the nervous system.

Analysis of variance is commonly used in morphometry in order to ascertain differences in parameters between several populations. Failure to detect significant differences between populations (type II error) may be due to suboptimal sampling and lead to erroneous conclusions; the concept of statistical power allows one to avoid such failures by means of an adequate sampling. Several examples are given in the morphometry of the nervous system, showing the use of the power of a hierarchical analysis of variance test for the choice of appropriate sample and subsample sizes. In the first case chosen, neuronal densities in the human visual cortex, we find the number of observations to be of little effect. For dendritic spine densities in the visual cortex of mice and humans, the effect is somewhat larger. A substantial effect is shown in our last example, dendritic segmental lengths in monkey lateral geniculate nucleus. It is in the nature of the hierarchical model that sample size is always more important than subsample size. The relative weight to be attributed to subsample size thus depends on the relative magnitude of the between observations variance compared to the between individuals variance.

Aging↗
PubMed2001

Visual analysis of variance: a tool for quantitative assessment of fMRI data processing and analysis.

Analysis of variance (ANOVA) is widely used for the study of experimental data. Here, the reach of this tool is extended to cover the preprocessing of functional magnetic resonance imaging (fMRI) data. This technique, termed visual ANOVA (VANOVA), provides both numerical and pictorial information to aid the user in understanding the effects of various parts of the data analysis. Unlike a formal ANOVA, this method does not depend on the mathematics of orthogonal projections or strictly additive decompositions. An illustrative example is presented and the application of the method to a large number of fMRI experiments is discussed.

Analysis of Variance↗
PubMed1992

Presynaptic inhibition of excitatory synaptic transmission by adenosine in rat hippocampus: analysis of unitary EPSP variance measured by whole-cell recording.

We have utilized the favorable signal-to-noise ratios provided by whole-cell recording, combined with variance analysis, to determine the pre- or postsynaptic actions of a variety of manipulations on unitary EPSPs evoked by low-intensity stimulation of afferents to CA1 pyramidal neurons in slices of hippocampus. Estimates of quantal content (mcv) were determined by calculating the ratio of the squared average unitary EPSP amplitude (determined from 150-275 responses) to the variance of these responses (M2/sigma 2), while quantal amplitudes (qcv) were estimated by calculating the ratio of the response variance to average EPSP size (sigma 2/M). Estimates of mcv were highly correlated with those determined using the method of failures (mf). With paired stimulation (50 msec interpulse interval) there was a significant facilitation of the second unitary EPSP, accompanied by an increase in mcv, but not qcv, suggesting that this facilitation was of presynaptic origin. Superfusion of hippocampal slices with various concentrations of adenosine, the A1-selective adenosine receptor agonist cyclohexyladenosine, or the Ca2+ channel blocker cadmium significantly reduced average unitary EPSP amplitudes and mcv, without significantly altering qcv, suggesting a presynaptic locus for this inhibition. The 50% effective concentration for the apparent presynaptic action of adenosine on mcv in the present study (5.7 microM; 95% confidence limits = 4.2-7.7 microM) was significantly lower than its EC50 for reducing conventional, large EPSPs (33 microM; recorded with high-resistance microelectrodes), or extracellular field EPSPs (29 microM), as previously reported by this laboratory. The glutamate receptor antagonist 6,7-dinitroquinoxaline-2,3-dione (DNQX) reduced average unitary EPSP amplitudes; in contrast to the above manipulations, it had no effect on mcv, but significantly altered qcv, which is consistent with its presumed postsynaptic mechanism of action. We conclude from these data that adenosine presynaptically reduces synaptic strength at Schaffer collateral-commissural synapses in the hippocampus by diminishing the number of quanta released, not by reducing the size of these individual quanta or postsynaptic sensitivity to excitatory neurotransmitter. These results suggest that the mechanism by which adenosine inhibits synaptic transmission in the hippocampus is similar, if not identical, to the mechanism by which it inhibits synaptic transmission at the neuromuscular junction.

Adenosine↗
PubMed2006

Effect of chiropractic care on heart rate variability and pain in a multisite clinical study.

OBJECTIVE: The purpose of this study is to investigate the effect of chiropractic care in a multiclinic setting on sympathetic and parasympathetic nervous system activities using heart rate variability (HRV) analysis. METHODS: Physicians of chiropractic in private practice were provided with an HRV device to perform analysis before and after chiropractic adjustments on 10 subjects. At each site, 8 subjects were monitored before and after a single chiropractic adjustment, and 2 additional patients were followed for a 4-week period with 2 HRV recordings per week. Patient information forms and a visual analog scale (VAS) questionnaire were completed both before and after each chiropractic adjustment. RESULTS: Data from 96 physicians were divided into single-visit and 4-week groups. After 1 chiropractic adjustment, pain as analyzed by VAS was reduced significantly from 3.7 +/- 2.2 to 2.1 +/- 2.0 (P < .001). The mean heart rate reduced from 76.7 +/- 12.7 to 74.3 +/- 12.4 (P < .01), the SD of normal-to-normal QRS increased from a range of 55.8 to 44.6 to a range of 60.6 to 47.2 (P < .001), the high-frequency component increased from 359 +/- 968 to 444 +/- 1069 (P < .01), the low-frequency component increased from 403 +/- 753 to 465 +/- 755 (P < .05), and the total power increased from 1063 +/- 1886 to 1265 +/- 2048 (P < .01). After 4 weeks of chiropractic adjustments, pain measured by the VAS was reduced significantly before and after each visit as analyzed by t tests, but the significant changes were not found using analysis of variance analysis. The reduction of pain from each treatment was not maintained over the 4 weeks of study period. The analysis of variance on the HRV 4-week data found that changes in the SD of normal-to-normal QRS, total power, and low-frequency components reached statistically significant levels (P < .05). The heart rate and the high-frequency component did not change significantly (P > .05). CONCLUSION: In this study, HRV and VAS changed in patients as a result of chiropractic care.

Autonomic Nervous System↗
PubMed2001

Effects of fluvoxamine and paroxetine on sleep structure in normal subjects: a home-based Nightcap evaluation during drug administration and withdrawal.

BACKGROUND: Acute and chronic administration of the selective serotonin reuptake inhibitors (SSRIs) have been widely reported to disrupt sleep in laboratory studies. This study examines the naturalistic, longitudinal effects of paroxetine and fluvoxamine on sleep quality in the home setting. METHOD: Fourteen healthy volunteers free of medical and neuropsychiatric symptoms entered a 31-day protocol: 7 days of drug-free baseline (days 1-7), 19 days of drug treatment (steady state during days 18-26), and 5 days of acute withdrawal (days 27-31). On day 8, the subjects were randomly assigned to receive either 100 mg/day of fluvoxamine or 20 mg/day of paroxetine (half receiving each drug) in divided morning and evening oral doses. Investigators remained blinded to drug assignment until all sleep data had been analyzed. Sleep was monitored using the Nightcap ambulatory sleep monitor. Four standard and 3 novel measures were computed and compared using multivariate analysis of variance, analysis of variance, and Bonferroni-corrected comparison of means. RESULTS: Sleep disruption was most clearly demonstrated using the novel measures eyelid quiescence index, rhythmicity, and eyelid movements per minute in non-rapid eye movement sleep, but was also apparent as determined by standard measures of sleep efficiency, number of awakenings, and sleep onset latency. Paroxetine disrupted sleep more than fluvoxamine, and paroxetine-induced sleep disruption persisted into the withdrawal phase. Rapid eye movement sleep was suppressed during treatment (especially for fluvoxamine) and rebounded during withdrawal (especially for paroxetine). CONCLUSION: We confirm laboratory polysomnographic findings of SSRI-induced sleep quality changes and demonstrate the Nightcap's efficacy as an inexpensive longitudinal monitor for objective sleep changes induced by psychotropic medication.

Adult↗
PubMed1998

Comparison of meta-analysis versus analysis of variance of individual patient data.

Meta-analysis is a method of synthesizing the results of independent studies. We consider the case in which there are multiple treatments and a control, with the goal of estimating the relative effect of each treatment based on continuous outcomes. Even when all data are available, rather than only summary data, it has become common to use meta-analytic estimators of treatment contrasts. Alternatively, we could use a two-way analysis of variance model with no interaction in which one factor is study and one factor is treatment. For the unbalanced case, we obtain the surprising result that the standard meta-analysis estimates of treatment contrasts are identical to the least squares estimators of treatment contrasts in the linear model. Because a meta-analysis of individual patient data can be considerably more costly in terms of data retrieval than a meta-analysis of summary data, this equivalence provides for cost-efficient analysis.

Analysis of Variance↗
PubMed1989

[BVC (bias to variance characteristic) analysis].

The average and variance of diagnostic rating scores obtained when many physicians read one image represents the bias to variance characteristics (BVC) in image diagnosis and are parameters reflecting the quality of image that are the objects, and the physicians' characteristics in image diagnosis. They were experimentally confirmed. Combination of the results of BVC analysis with ROC analysis was shown to clarify the structure and origin of the ROC curve and to improve the interpretation of the ROC curve that was the final results of evaluation. Furthermore, it was suggested the if BVC was used as complementary data in a case study, there was a possibility of it being useful for clarify the clinical, technical and physical factors affecting the results of image diagnosis.

Diagnostic Imaging↗
PubMed2004

Statistics review 9: one-way analysis of variance.

This review introduces one-way analysis of variance, which is a method of testing differences between more than two groups or treatments. Multiple comparison procedures and orthogonal contrasts are described as methods for identifying specific differences between pairs of treatments.

Analysis of Variance↗
PubMed2001

Genome-wide linkage analyses of total serum IgE using variance components analysis in asthmatic families.

Variance components models were used to analyze total IgE levels in families ascertained though the Collaborative Study of the Genetics of Asthma (CSGA) using a genome-wide array of polymorphic markers. While IgE levels are known to be associated with clinical asthma and recognized to be under strong genetic control (here the heritability was estimated at 44-60% in the three racial groups), specific genes influencing this trait are still largely unknown. Multipoint analysis of 323 markers yielded little indication of specific regions containing a trait locus controlling total serum IgE levels (adjusted for age and gender). Although a number of regions showed LOD statistics above 1.5 in Caucasian families (chromosome 4) and in African-American families (chromosomes 2 and 4), none yielded consistent evidence in all three racial groups. Analysis of total IgE adjusted for gender, age and Allergy Index (a quantitative score of skin test sensitivity to 14 common aeroallergens) was conducted on these data. In this analysis, a much stronger signal for a trait locus controlling adjusted log[total IgE] was seen on the telomeric end of chromosome 18, but only in Caucasian families. This region accounted for most of the genetic variation in log[total IgE], and may represent a quantitative trait locus for IgE levels independent of atopic response. Oligogenic analysis accounting simultaneously for the contribution of this locus on chromosome 18 and other chromosomal regions showing some evidence of linkage in these Caucasian families (on chromosomes 2, 4 and 20) failed to yield significant evidence for interaction.

Asthma↗