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At least 1,135 records · Page 63Linked to original sources
PubMedDate not supplied

Incomplete quality of life data in randomized trials: missing forms.

Analysing quality of life (QOL) data may be complicated for several reasons, such as: repeated measures are obtained; data may be collected on ordered categorical responses; the instrument may have multidimensional scales, and complete data may not be available for all patients. In addition, it may be necessary to integrate QOL with length of life. The major undesirable effects of missing data, in QOL research, are the introduction of biases due to inadequate modes of analysis and the loss of efficiency due to reduced sample sizes. Currently, there is no standard method for handling missing data in QOL studies. In fact, there are very few references to methods of handling missing data in this context. The aim of this paper is to provide an overview of methods for analysing incomplete longitudinal QOL data which have either been presented in the QOL literature or in the missing data literature. These methods of analysis include complete case, available case, summary measures, imputation and likelihood-based approaches. We also discuss the issue of bias and the need for sensitivity analyses.

Bias↗
PubMed1996

Measuring the technical efficiency of psychiatric hospitals.

The purpose of this study was to assess the efficiency of psychiatric hospitals. Data Envelopment Analysis was used to examine the technical efficiency for sample of the 85 profit and not-for-profit psychiatric hospitals. Results suggests reduction of excessive resource use by all inefficient facilities would result, on average, in a $7.2 million dollar savings in operational expenses, a total of 1715 FTEs in labor reductions, and a reduction of 1129 beds.

Cost-Benefit Analysis↗
PubMed2006

[Abecedary of the "Annales". Part 14].

The terms included and detailed in the present part are: Median, Medline, MeSH, meta-analysis, fixed effects model, random effects model, Mean.

Clinical Trials as Topic↗
PubMed2000

Identifying the maximum safe dose: a multiple testing approach.

Identifying the maximum safe dose (MAXSD) is an objective of both randomized clinical dose-finding studies for the safety endpoint and toxicological studies. MAXSD is defined as the highest experimental dose with no significant increased safety effect relative to the placebo or control group. In safety assessment, the primary control of the false-negative error rate is more important than that of the false-positive rate. Therefore, we propose a multiple testing procedure for equivalence in the many-to-one design with a priori ordered contrasts (shifted control vs. dose), where the acceptable risk delta is defined in advance. Tests for shifted and ratio hypotheses are presented and discussed.

Animals↗
PubMed1991

Methods of data analysis in the emergency medicine literature.

The authors hypothesized that data analysis in the current emergency medicine literature uses relatively few methods and sought to determine the frequency distributions of each method of analysis. The authors defined their population as original contributions in three refereed emergency medicine journals from September, 1985 through July, 1989. Letters to the editor, brief reports, reviews, and case reports were excluded. The authors reviewed 250 randomly selected articles and identified the method(s) of data analysis in each. The absolute frequency distribution of statistics were as follows: descriptive statistics only, 31%; contingency tables, 35% (chi 2, 28.4%; Fisher's exact test, 13.2%; McNemar's test, 0.4%); Student's t-test, 34%; ANOVA/ANCOVA, 12%; regression techniques, 8% (simple linear regression, 4.0%; multiple regression, 3.6%; logistic regression, 1.6%); nonparametric tests, 7% (Mann-Whitney, 2.8%; Wilcoxon, 2.4%; Dunnett, 0.8%; Kolmogorv-Smirnov, 0.4%; Kruskal-Wallis, 0.4%); multiple comparisons, 6% (Scheffé, 4.4%; Newman-Keuls, 2.0%); correlation techniques, 4% (Pearson product-moment correlation coefficient, 2.8%; Kendall's tau, 0.8%; Spearman's rho, 0.4%); confidence intervals, 2%. Correction techniques were used in 9% (Dunn-Bonnferoni, 4.8%; Yates correction, 4.4%). No statistics were found in 2% of the articles reviewed. Five statistical methods account for the vast majority (97% cumulative) of statistical uses in emergency medicine literature. This information should prove useful in deciding which tests should be emphasized in educating emergency physicians.

Curriculum↗
PubMed2004

Capture-recapture is a potentially useful method for assessing publication bias.

OBJECTIVES: Publication bias is a problem in systematic reviews of randomized controlled trials. The aim of this study was to assess the influence of publication bias in a systematic review of the effectiveness of Progressive Resistance Training (PRT) in older people. STUDY DESIGN AND SETTING: The relevant studies were ascertained from three sources: electronic databases, experts, and handsearching. Capture-recapture, visual inspection of funnel plots, two statistical tests, and two methods that make adjustments for publication bias, were employed to check the robustness of the conclusions of the systematic review. RESULTS: The methods employed gave broadly consistent results. Capture-recapture estimated that 3 (95% CI ) relevant studies were missed, while Trim and Fill suggested 16 studies had been missed. Both Egger's test for bias and a funnel plot regression approach suggested that publication bias was present. A selection model approach suggested that the funnel plot asymmetry observed may not be entirely due to publication bias. CONCLUSION: Capture-recapture is a potentially useful method for assessing publication bias. Further research in the form of simulation studies is required, using a variety of scenarios to investigate the extent to which each method approximates the truth.

Aged↗