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PubMed1996

Gallbladder carcinoma: a video image analysis of AgNOR distribution and its relation to tumour stage and grade.

The amount and distribution of interphase argyrophilic nucleolar organizer regions (AgNORs) was studied in 51 gallbladder surgical specimens including 32 primary carcinomas, 10 adenomas and 9 cases of chronic cholecystitis with calculi. The mean nuclear AgNOR area (NORA) and the AgNOR distribution score (NORDS), i.e. the percentage of cells carrying nucleolar aggregates with more than 6 distinct silver dots, were evaluated in 200 epithelial nuclei per specimen by means of automated image analysis and direct counting respectively. Statistical analysis (variance analysis and Student-Neuman-Keuls' test) performed on the pooled mean AgNOR values showed a significant difference (p < 0.001) between carcinomas and non-carcinomatous lesions. Both NORA and NORDS highly discriminated carcinomas with histopathological grade 4 versus cases with grade 1, 2 or 3 (p < 0.001); a less statistically significative p value (< 0.05) was encountered when NORDS values of well differentiated grade 1 carcinomas and adenomas were compared. The NORA parameter permitted the discrimination of stage IV versus stage I carcinomas (p < 0.001), while carcinomas in stage IV and those in stage II were distinguished with a p < 0.05; the NORDS parameter allowed also to distinguish stage IV from both stage I or II tumours (p < 0.001). Our results indicate that the above-mentioned AgNOR parameters may be utilized as additional, more objective quantitative criteria in the clinical-pathological assessment of the outcome of gallbladder carcinomas.

Adenoma↗
PubMed2001

Expression profile of epidermal differentiation complex genes in normal and anal cancer cells.

Anal cancer originates from a peculiar histological region and provides a useful model for investigating alterations in proliferation and/or differentiation of neoplastic keratinocytes. Epidermal differentiation complex (EDC) genes, which form one of the major gene clusters in the human genome, are involved in the terminal differentiation of epithelial cells and in many instances have been implicated in epithelial tumours. We constructed a DNA macroarray capable of characterising the expression profiles of the entire EDC gene complex in normal mucosa and anal cancer biopsies of seven unrelated patients. Brain tissue and cultured keratinocytes were used as controls. All anal cancer samples showed expression profiles in which none of the EDC genes was silent, as evaluated by phosphor-imager analysis. Variance analysis showed significantly lower expression of SPRR2 with respect to SPRR1 or SPRR3, and significantly higher expression of S100A8 than of other S100A subfamily members. At hierarchical clustering analysis, the four basaloid anal cancer cases conglomerated in the top five positions. The macroarray method used by us provides the first demonstration of the expression profile of the EDC gene family in anal cancer, and is capable of producing significant information on the subgrouping of epithelial tumours such as anal cancer.

Adult↗
PubMedDate not supplied

[Spinal anesthesia in cesarean section: 1% versus 0.5% hyperbaric bupivacaine].

AIM: To compare the quality of anesthesia produced by the intrathecal administration of equivalent doses of 0.5% and 1% hyperbaric bupivacaine in patients undergoing cesarian section. EXPERIMENTAL DESIGN: A prospective, comparative and randomised clinical study. SETTING: Anesthesia Unit-Non-university civil hospital. PATIENTS: 50 patients undergoing elective or emergency cesarian section randomly assigned to two groups of 25 patients each. SURGERY: After prehydration, subarachnoid access was achieved through space L2-L3 or L3-L4 using a 24G Sprotte's needle with patients in right hand lateral decubitus. Patients in group A were injected with 1.25 ml of 1% hyperbaric bupivacaine and those in group B with 2.5 ml of 0.5% hyperbaric bupivacaine (12.5 mg). Patients were positioned immediately in partial decubitus on their left hand sides and ephedrine infusion, or if required i.v. bolus, was commenced to counter hypotension (SAP < 80% basal). MEASUREMENTS: ECG, pulse measurement, arterial pressure with non-invasive method, metameric level of analgesia (pin prick), motor block of lower limbs (Bromage's scale), time lapsed between induction of anesthesia and extraction of neonate, Apgar score, quantity of ephedrine used, duration of surgery, respiratory complications, insufficient analgesia, resolution of motor block, any postspinal cephalea. STATISTICAL ANALYSIS: Variance analysis, Student's t-test, chi 2. RESULTS: Both solutions guaranteed satisfactory intraoperative analgesia in 96% of cases. No statistically significant differences were noted between the two groups relating to the maximum duration of analgesia, the extent of motor block, induction times and regression, incidence of complications. CONCLUSIONS: No important difference was observed in the quality of the anesthesia obtained using the intrathecal administration of equivalent doses of 1% and 0.5% solutions of hyperbaric bupivacaine in patients undergoing cesarian section. In view of the possible relationship between the neurotoxicity of local anesthetics and the concentration of the solution used for spinal anesthesia, it is to be hoped that less concentrated solutions of hyperbaric bupivacaine will be introduced in Italy compared to the 1% solution currently available.

Adult↗
PubMed1978

[Study of statistical test connections in non-orthogonal analysis of variance].

In the Analysis of Variance, we quite often split up the model to test different hypotheses about the model. However, when we analyse the results, we must not forget that the statistics used for the tests are not stochastically independent, either for an orthogonal design, because the test statistics have the same denominator, or for non-orthogonal design. In the latter case, test statistics have not only the same denominator but also not-independent numerators. The links between test statistics have been studied for orthogonal designs (Dall'Aglio, 1962) and for symmetrical Incomplete Block Design (Ballas and Webster, 1966). We shall give here results for the general case of the Analysis of Variance, treat more particularly the case of the Incomplete Block Design and show the joint distribution of two test statistics and, more simply, their correlation coefficient.

Analysis of Variance↗
PubMed1977

[Repeated characterization, analysis of variance limitation and discrimination analysis classification of EEG-activity patterns in human sleep].

1. To describe quantitatively and to deliminate nine EEG sleep patterns, mean values and standard deviations of abundances of the frequencies 0.8 ... 1.8 c/sec, 2...3.5 c/sec, 4...13c/sec, 14 to 17 c/sec, 18 to 22 c/sec, and 23 to 40 c/sec as well as of the average amplitudes in selected frequency ranges were calaculated and the distributions represented. 2. All nine EEG activity patterns could be separated by means of univariate and multivariate analyses of variance on the basis of all 28 as well as the 17 indispensable variables. 3. In the course of a stepwise reduction of variables within the framework of a linear discriminant analysis an optimal set of 17 variables was determined for the separation of the patterns, comprising: the percent quantity of the frequencies 0.8 ... 3.5 c/sec, 7 ... 9 c/sec and 18 to 40 c/sec as well as the average amplitudes in the frequency ranges 0.8 to 3.5 c/sec and 7.5 to 40 c/sec. 4. By linear regression analyses it could be shown that the sleep scording system used, can be reflected on an interval scale with the aid of discriminant functions; this can be achieved on the basis of the optimal set of variables as well as of the five most indispensable variables. 5. Finally the degree of the objectivity of the scoring procedures was demonstrated. Advantages and disadvantages of sleep scoring systems were discussed and possibilities of the utilization of results suggested, also in respect to the further development of the automatic recognition of EEG activity patterns.

Analysis of Variance↗
PubMed2003

The aesthetic earlobe: classification of lobule ptosis on the basis of a survey of North American Caucasians.

North American Caucasian male subjects (n = 59) and female subjects (n = 72) were surveyed, to investigate earlobe height preferences that could serve as guidelines for aesthetic earlobe surgical procedures and reconstructions. Subjects were asked to rank their preferences for variously shaped earlobes in life-size-scaled sketched male and female profiles. Earlobe heights were varied on the basis of previously established anatomical landmarks, including the intertragal notch, the most caudal anterior attachment of the earlobe to the cheek skin (the otobasion inferius), and the most caudal extension of the earlobe-free margin (the subaurale). While the intertragal notch-to-otobasion inferius distance (range, 5 to 20 mm) and otobasion inferius-to-subaurale distance (range, 0 to 20 mm) varied, all other facial and ear anthropometric measurements were held constant. Each of the rank orders for the female and male facial profiles completed by the female and male subjects demonstrated statistical significance, as determined by one-way analysis of variance analysis of ranks (p < 0.001 for all four groups). No difference was noted between the two sexes' rank orders for either sex (p > 0.05). Therefore, analysis of the combined male and female preferences for each sex was completed with one-way analysis of variance analysis of ranks (p < 0.001 and p < 0.001) and a post hoc Dunn's test, to delineate significant preference differences between subgroups with respect to the intertragal notch-to-otobasion inferius and otobasion inferius-to-subaurale distances. Both female and male earlobe intertragal notch-to-otobasion inferius distances were preferred at either 5, 10, or 15 mm, more so than at 20 mm (p < 0.05 for all female and male comparisons). Furthermore, both female and male earlobe otobasion inferius-to-subaurale distances were preferred, in descending order, at 5 mm > 10 mm > 0 mm > 15 mm > 20 mm (p < 0.05 for all female and male comparisons). On the basis of the findings of this survey, the first classification of earlobe ptosis (based on otobasion inferius-to-subaurale distances), as well as a criterion for earlobe pseudoptosis (intertragal notch-to-otobasion inferius distance of greater than 15 mm), is presented. These findings suggest a role for independent assessment of the lobule length with respect to its anteriorly attached cephalad component (intertragal notch-to-otobasion inferius distance) and its free-margin caudal component (otobasion inferius-to-subaurale distance).

Aging↗
PubMedDate not supplied

Analysis of variance is easily misapplied in the analysis of randomized trials: a critique and discussion of alternative statistical approaches.

Analysis of variance (ANOVA) is a statistical method that is widely used in the psychosomatic literature to analyze the results of randomized trials, yet ANOVA does not provide an estimate for the difference between groups, the key variable of interest in a randomized trial. Although the use of ANOVA is frequently justified on the grounds that a trial incorporates more than two groups, the hypothesis tested by ANOVA for these trials--"Are all groups equivalent?"--is often scientifically uninteresting. Regression methods are not only applicable to trials with many groups, but can be designed to address specific questions arising from the study design. ANOVA is also frequently used for trials with repeated measures, but the consequent reporting of "group effects," "time effects," and "time-by-group interactions" is a distraction from statistics of clinical and scientific value. Given that ANOVA is easily misapplied in the analysis of randomized trials, alternative approaches such as regression methods should be considered in preference.

Analysis of Variance↗
PubMed1995

Comparison of analysis of variance and maximum likelihood based path analysis of twin data: partitioning genetic and environmental sources of covariance.

In order to investigate currently used model fitting strategies for twin data, analysis of variance (ANOVA) and path-maximum-likelihood (PATH-ML) methods of analyzing twin data were compared using simulation studies of 50 monozygotic (MZ) and 50 dizygotic (DZ) twin pairs. Phenotypic covariance was partitioned into additive genetic effects (A), environmental effects common to cotwins (C), and environmental variance unique to individuals (E). ANOVA and PATH-ML had identical power to detect total covariance. The PATH-ML AE model was much more powerful than ANOVA comparisons of rMZ and rDZ to detect A. However, to be unbiased, the AE model requires the assumption that C = 0.0. To allow use of the AE model to estimate A, the null hypothesis C = 0.0 is tested by comparing the goodness of fit of the ACE and AE models. Simulation of 50 MZ and 50 DZ pairs revealed that C must be greater than 55% of total variance before the null hypothesis would be rejected (P < 0.05) 80% of the time. Several recent publications were reviewed in which the null hypothesis C = 0.0 was accepted and apparently upwardly biased estimates of A, containing C, were presented with unrealistic P values. It was concluded that use of the AE model to estimate A gives an inflated view of the power of relatively small twin studies. It was recommended that ANOVA or comparison of the ACE and CE PATH-ML models be used to estimate and test the significance of A as neither requires that C = 0.0.

Analysis of Variance↗
PubMed1981

Interpretation of research data: analysis of variance.

The use of analysis of variance (ANOVA) in research studies is discussed. ANOVA is a set of procedures used in testing for differences between means that partitions the total variation found in a sample of score values into "explained" and "error" components. The test statistic used in ANOVA is the F ratio, and probabilities are found in tables of F distributions similar to t, z, or x2 tables. Equations used in ANOVA procedures and exercises for computational practice are given. Design of experiments that facilitate ANOVA use is discussed, as is the difference between t tests and F tests. Total sum of squares, mean squares, and squared correlation ratio are described.

Analysis of Variance↗
PubMed2006

Analysis of variance of microarray data.

Analysis of variance (ANOVA) is an approach used to identify differentially expressed genes in complex experimental designs. It is based on testing for the significance of the magnitude of effect of two or more treatments taking into account the variance within and between treatment classes. ANOVA is a highly flexible analytical approach that allows investigators to simultaneously assess the contributions of multiple factors to gene expression variation, including technical (dye, batch) effects and biological (sex, genotype, drug, time) ones, as well as interactions between factors. This chapter provides an overview of the theory of linear mixture modeling and the sequence of steps involved in fitting gene-specific models and discusses essential features of experimental design. Commercial and open-source software for performing ANOVA is widely available.

Analysis of Variance↗
PubMed2001

Improved statistical inference from DNA microarray data using analysis of variance and a Bayesian statistical framework. Analysis of global gene expression in Escherichia coli K12.

We describe statistical methods based on the t test that can be conveniently used on high density array data to test for statistically significant differences between treatments. These t tests employ either the observed variance among replicates within treatments or a Bayesian estimate of the variance among replicates within treatments based on a prior estimate obtained from a local estimate of the standard deviation. The Bayesian prior allows statistical inference to be made from microarray data even when experiments are only replicated at nominal levels. We apply these new statistical tests to a data set that examined differential gene expression patterns in IHF(+) and IHF(-) Escherichia coli cells (Arfin, S. M., Long, A. D., Ito, E. T., Tolleri, L., Riehle, M. M., Paegle, E. S., and Hatfield, G. W. (2000) J. Biol. Chem. 275, 29672-29684). These analyses identify a more biologically reasonable set of candidate genes than those identified using statistical tests not incorporating a Bayesian prior. We also show that statistical tests based on analysis of variance and a Bayesian prior identify genes that are up- or down-regulated following an experimental manipulation more reliably than approaches based only on a t test or fold change. All the described tests are implemented in a simple-to-use web interface called Cyber-T that is located on the University of California at Irvine genomics web site.

Bayes Theorem↗
PubMed2006

College women's experience of stalking: mental health symptoms and changes in routines.

BACKGROUND: Stalking is a serious public health and societal concern affecting many college women. PURPOSE: The purpose of this study was to explore college women's experiences of stalking. The specific aims were to compare victims and nonvictims on physical and mental health indicators and to identify lifestyle changes made in response to being stalked. METHODS: In this cross-sectional design, 601 women from two universities completed a stalking questionnaire, a mental health screening tool, and an injury checklist. Data analysis included frequencies, multivariate analysis of variance, analysis of variance, and chi(2) analysis. RESULTS: A quarter of the sample reported experiencing stalking, most often by an intimate or dating partner. Individuals who reported experiencing stalking reported significantly more mental health symptoms and lower perceived physical health status than individuals who did not. Victims reported changing routines, behaviors, and activities. CONCLUSIONS: Psychiatric nurses must be knowledgeable about stalking and its impact on health. Nurses can provide support, services, and community referrals.

Activities of Daily Living↗
PubMed1982

Numerical evaluation of cytologic data. XI. Nested designs in multivariate analysis of variance.

Nested designs in multivariate analysis of variance allow the investigator to assess at what stages in an experimental procedure variability enters and to what extent. When employed in conjunction with a fixed-effects level in the design, a mixed model results, which provides the appropriate significance tests for the fixed-level effect; e.g., differences in cells between control patients and treated patients must be tested against the patient-to-patient variability, not against the cell-to-cell variability. A worked example for a three-level, mixed-model nested design is given, including the significance tests.

Analysis of Variance↗