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At least 1,153 records · Page 64Linked to original sources
PubMed1998

[Current use of statistical methods in five core Chinese medical journals].

OBJECTIVE: To determine the frequency of statistical techniques used in Chinese medical journals, types of statistical errors present, and trends over a 10-year period. METHODS: We reviewed the statistical methods used in all original articles published in 5 leading journals in 1985 (n = 640) and 1995 (n = 954). RESULTS: Compared with 1985, significant improvement was seen in 1995. The proportion of papers using statistical tests increased from 40% to 60% (chi 2 = 60.9, P < 0.01), and more sophisticated statistical methods were used. Of those articles using statistics, the proportion using appropriate methods increased from 22% to 46% (chi 2 = 45.3, P < 0.01). In both years, the most commonly used statistical methods were t tests and contingency tables. The most common errors were presentation of P values without specifying the test used, use of multiple t tests instead of ANOVAs, and use of unpaired t tests when paired tests were required. CONCLUSION: The use of statistical methods in Chinese medical journals is improving, and by 1995, the frequency of using statistical methods in published articles was similar to that in other journals around the world. However, the lack of or inappropriate sue of statistics remains a serious problem.

China↗
PubMed1994

Epidemics: models and data.

"The problems of understanding and controlling disease raise a range of challenging mathematical and statistical research topics, from broad theoretical issues to specific practical ones. In particular, recent interest in acquired immune deficiency syndrome has stimulated much progress in diverse areas of epidemic modelling, particularly with regard to the treatment of heterogeneity, both between individuals and in mixing of subgroups of the population. At the same time better data and data analysis techniques have become available, and there have been exciting developments in relevant theory.... This progress in specific areas is now being matched by interdisciplinary cooperation aimed at elucidating relationships between the widely varying types of model that have been found useful, to determine their strengths and limitations in relation to basic aims such as understanding, prediction, and evaluation and implementation of control strategies."

Acquired Immunodeficiency Syndrome↗
PubMed2000

Statistics in medical journals: some recent trends.

I review some areas of medical statistics that have gained prominence over the last 5-10 years: meta-analysis, evidence-based medicine, and cluster randomized trials. I then consider several issues relating to data analysis and interpretation, many relating to the use and misuse of hypothesis testing, drawing on recent reviews of the use of statistics in medical journals. I also consider developments in the reporting of research in medical journals.

Data Interpretation, Statistical↗
PubMed2005

Direct likelihood analysis versus simple forms of imputation for missing data in randomized clinical trials.

BACKGROUND: In many clinical trials, data are collected longitudinally over time. In such studies, missingness, in particular dropout, is an often encountered phenomenon. METHODS: We discuss commonly used but often problematic methods such as complete case analysis and last observation carried forward and contrast them with broadly valid and easy to implement direct-likelihood methods. We comment on alternatives such as multiple imputation and the expectation-maximization algorithm. RESULTS: We apply these methods in particular to data from a study with continuous outcomes. The outcomes are modelled using a general linear mixed-effects model. The bias with CC and LOCF is established in the case study and the advantages of the direct-likelihood approach shown. CONCLUSIONS: We have established formal but easy to understand arguments for a shift towards a direct-likelihood paradigm when analysing incomplete data from longitudinal clinical trials, necessitating neither imputation nor deletion.

Data Collection↗
PubMed2005

[Presentation of statistical analysis in the Journal of the Norwegian Medical Association].

The present paper describes guidelines for the presentation of statistical analysis in manuscripts submitted to the Journal of the Norwegian Medical Association, in order to ensure a reasonable standard of statistic presentation in the journal. The paper is a supplement to the guidelines for authors in the journal and should not be used as replacement for statistics manuals.

Guidelines as Topic↗
PubMed2004

Controversies concerning randomization and additivity in clinical trials.

'As ye randomise so shall ye analyse', is one way of describing Fisher's defence of randomization. Yet, when it comes to clinical trials we nearly always randomize but we rarely analyse the way we randomize and Fisher himself was no exception. Two controversies involving Fisher in the 1930s are discussed: one with Neyman concerning additivity and the other with Student concerning randomization. Their relevance today is considered, as is whether randomization inference in clinical trials is dead and whether modelling rules the day, whether minimization is an acceptable procedure and to what extent trialists confuse experiments with surveys. It will be maintained that a number of different possible purposes of clinical trials have been confused because in the case of the general linear model, under strong additivity, they can all be satisfied by a single analysis. More generally, however, this is not the case.

Data Interpretation, Statistical↗
PubMed1995

Dose response studies. II. Analysis and interpretation.

The primary focus of this paper is to examine analysis strategies for parallel, randomized dose response studies with particular emphasis on identifying the minimum effective dose. Such studies have become a standard for drug development in the pharmaceutical industry. Particular attention is paid to ANOVA followed by multiple comparison procedures with some additional discussion of the utility or regression models. When there are three or fewer dose groups and a placebo in a study, ANOVA techniques are preferred; with a larger number of dose groups, regression analysis has greater utility and reliability. Analysis of factorial dose response studies is reviewed only slightly as this is an emerging area of interest, and further development is necessary.

Data Interpretation, Statistical↗
PubMed1989

Usage of statistics in the surgical literature and the 'orphan P' phenomenon.

The statistics used in 240 surgical publications were reviewed. Basic parametric statistics were used in 60% of the publications; 21% of publications failed to document a measure of central tendency, 11% of publications contained an undefined '+/-' notation, and 10% of publications did not state the type of evaluative statistic that was used to calculate a P value, that is, an 'orphan P'. These results indicate the need for wider education about the use of descriptive and basic parametric statistics. It is impossible to evaluate the surgical literature critically without these skills.

Australia↗