Abhaya Indrayan

Monte Carlo comparison of six hierarchical clustering methods on random data

There is mounting evidence to suggest that the complete linkage method does the best clustering job among all hierarchical agglomerative techniques, particularly with respect to misclassification in samples from known multivariate normal distributions. However, clustering methods are notorious for discovering clusters on random data sets also. We compare six agglomerative hierarchical methods on univariate random data from uniform and standard normal distributions and find that the complete linkage method generally is best in not discovering false clusters. The criterion is the ratio of number of within-cluster distances to number of all distances at most equal to the maximum within-cluster distance.

Demystifying LMS and BCPE methods of centile estimation for growth and other health parameters

Lambda-Mu-Sigma and Box-Cox Power Exponential are popular methods for constructing centile curves but are difficult to understand for medical professionals. As a result, the methods are used by experts only. Non-experts use software as a blackbox that can lead to wrong curves. This article explains these methods in a simple non-mathematical language so that medical professionals can use them correctly and confidently.

Reporting quality of multivariable logistic regression in selected Indian medical journals

BACKGROUND Use of multivariable logistic regression (MLR) modeling has steeply increased in the medical literature over the past few years. Testing of model assumptions and adequate reporting of MLR allow the reader to interpret results more accurately. AIMS To review the fulfillment of assumptions and reporting quality of MLR in selected Indian medical journals using established criteria. SETTING AND DESIGN Analysis of published literature. MATERIALS AND METHODS Medknow.com publishes 68 Indian medical journals with open access. Eight of these journals had at least five articles using MLR between the years 1994 to 2008. Articles from each of these journals were evaluated according to the previously established 10-point quality criteria for reporting and to test the MLR model assumptions. STATISTICAL ANALYSIS SPSS 17 software and non-parametric test (Kruskal-Wallis H, Mann Whitney U, Spearman Correlation). RESULTS One hundred and nine articles were finally found using MLR for analyzing the data in the selected eight journals. The number of such articles gradually increased after year 2003, but quality score remained almost similar over time. P value, odds ratio, and 95% confidence interval for coefficients in MLR was reported in 75.2% and sufficient cases (>10) per covariate of limiting sample size were reported in the 58.7% of the articles. No article reported the test for conformity of linear gradient for continuous covariates. Total score was not significantly different across the journals. However, involvement of statistician or epidemiologist as a co-author improved the average quality score significantly (P=0.014). CONCLUSIONS Reporting of MLR in many Indian journals is incomplete. Only one article managed to score 8 out of 10 among 109 articles under review. All others scored less. Appropriate guidelines in instructions to authors, and pre-publication review of articles using MLR by a qualified statistician may improve quality of reporting.

Statistical fallacies in orthopedic research

Background: A large number of statistical fallacies occur in medical research literature. These are mostly inadvertent and occur due to lack of understanding of the statistical concepts and terminologies. Many researchers do not fully appreciate the consequence of such fallacies on the credibility of their report. Materials and Methods: This article provides a general review of the issues that could give rise to statistical fallacies with focus on orthopedic research. Some of this is based on real-life literature and some is based on the actual experiences of the author in dealing with medical research over the past three decades. The text is in teaching mode rather than research mode. Results: Statistical fallacies occur due to inadequate sample that is used for generalized conclusion; incomparable groups presented as comparable; mixing of two or more distinct groups that in fact require separate consideration; misuse of percentages, means and graphs; incomplete reporting that suppresses facts; ignoring reality and depending instead on oversimplification; forgetting baseline values that affect the outcome; misuse of computer packages and use of black-box approach; misuse of P-values that compromises conclusions; confusing correlation with cause-effect; and interpreting statistical significance as medical significance. Conclusion: Mere awareness of the situations where statistical fallacies can occur may be adequate for researchers to sit up and take note while trying to provide a credible report.

Statistical medicine: An emerging medical specialty

A large number of statistical tools are now used for medical decision in the core activities of diagnosis, treatment and prognosis. These tools provide undeniable help in improving medical outcomes. Prominent among them are uncertainty measurement by probability, medical indicators and indexes, reference ranges, and scoring systems. In addition are tools such as odds ratio, sensitivity, specificity and predictivities, area under the ROC curve, likelihood ratios, and cost-benefit analysis that are commonly applied in medical research but have implications for day-to-day clinical activities. These tools have so completely integrated into medical practice that statistical medicine by itself can stand alone as a medical specialty. Time has arrived to recognize statistical medicine as a medical specialty.

Evaluation of quality of multivariable logistic regression in Indian medical journals using multilevel modeling approach

Background: Availability of user-friendly statistical software has increased the application of multivariable logistic regression (MLR) in the medical journal many fold. The reporting quality in terms of checking assumptions, model building strategies, proper coding, and report format need proper care and attention to communicate correct and reliable model results. Objective: The objective of this article is to evaluate the quality of MLR article based on 10-point well establish criteria and to study the factors that may influence the quality. Methods: Study included PubMed indexed Indian medical journals as on March 2010 and published at least ten original articles that applied MLR during 10 years was included in the study. Multilevel modeling was applied to assess the role of journal and article attributes on MLR quality. Results: Twelve out of 39 Indian PubMed indexed journals fulfilled the inclusion criterion. Of a total 5599 original articles in these journals, 262 (4.68%) applied MLR in their study. Conformity of linear gradient assumption for continuous covariate was the least fulfilled criterion. One-third of the MLR articles involved statistician or epidemiologist as co-author, and almost same number of MLR articles′ first author was from outside India. The trend of 10-point criteria remained consistent although the number of MLR articles increased over the period. The average quality score was 3.78 (95% confidence interval: 2.97-4.60) out of a possible 10. Larger sample size, involvement of statistician as co-author, non-Indian as the first author, and use of SAS/STATA software increased the quality of MLR articles. Conclusions: The quality of MLR articles in Indian medical journals is lagging behind as compared to the quality of MLR articles published from the United States and Europe medical journals. Joint effort of editors, reviewers, and authors are required to improve the quality of MLR in Indian journals so that the reader gets the correct results.

Approximate Tests of Hypotheses in Regression Models with Grouped Data

Techniques for testing hypotheses about parameters in the regression models under the situation of grouped data are provided. A test statistic similar to conventional F statistic is considered. A simulation study performed for a few cases shows that the proposed statistic has an approximate F distribution and is useful in applications.