ABSTRACT
Background & objectives: Due to lack of appropriate statistical knowledge, published research articles contain various errors related to the design, analysis and interpretation of results in the area of biomedical research. If research contains statistical error, however, costly, it may be of no use and the purpose of the investigation gets defeated. Many biomedical research articles published in different peer reviewed journals may retain several statistical errors and flaws in them. This study aimed to examine the trend and status of application of statistics in biomedical research articles. Study design, sample size estimation and statistical measures are crucial components of a study. These points were evaluated in published original research articles to understand the use or misuse of statistical tools. Methods: Three hundred original research articles from the latest issues of selected 37 journals were reviewed. These journals were from the five internationally recognized publication groups (CLINICAL KEY, BMJ Group, WILEY, CAMBRIDGE and OXFORD) accessible through the online library of SGPGI, Lucknow, India. Results: Among articles assessed under present investigation, 85.3 per cent (n=256) were observational, and 14.7 per cent (n=44) were interventional studies. In 93 per cent (n=279) of research articles, sample size estimation was not reproducible. The simple random sampling was encountered rarely in biomedical studies even though none of the articles was adjusted by design effect and, only five articles had used randomized test. The testing of assumption of normality was mentioned in only four studies before applying parametric tests. Interpretation & conclusions: In order to present biomedical research results with reliable and precise estimates based on data, the role of engaging statistical experts need to be appreciated. Journals must have standard rules for reporting study design, sample size and data analysis tools. Careful attention is needed while applying any statistical procedure as, it will not only help readers to trust in the published articles, but also rely on the inferences the published articles draw.
ABSTRACT
Measurement scale is an important part of data collection, analysis, and presentation. In the data collection and data analysis, statistical tools differ from one data type to another. There are four types of variables, namely nominal, ordinal, discrete, and continuous, and their nature and application are different. Graphs are a common method to visually present and illustrate relationships in the data. There are several statistical diagrams available to present data sets. However, their use depends on our objectives and data types. We should use the appropriate diagram for the data set, which is very useful for easily and quickly communicating summaries and findings to the audience. In the present study, statistical data type and its presentation, which are used in the field of biomedical research, have been discussed.