Trends in Statistical Methods in Indian Library Science Research (2012-2022)

Abstract

This research surveys statistical techniques used in Indian Library and Information Science (LIS) studies by investigating 624 articles published during 2012-2022 in two prominent indexed journals-DJLIT and ALIS. The study classifies statistical techniques under descriptive techniques, parametric inferential techniques, nonparametric inferential techniques, and predictive techniques to gauge prevailing practices and identify trends. Analysis indicates descriptive statistics, in the form of frequency distributions and percentages are predominant in LIS research. Of inferential techniques, F-test/ANOVA and Chi-square tests were most common under parametric and nonparametric categories respectively. Predictive statistics were found to have had limited use, and of those, Pearson correlation was the most used technique. Reliability analysis was applied only in 6.09 % of articles, suggesting a large methodological gap. Microsoft Excel was the most used statistical package followed by SPSS, indicating low use of advanced analytical tools. Binary logistic regression analysis illustrated that multi-authored papers and papers with academic affiliations were more likely to use predictive approaches, while foreign authors made greater use of advanced statistical methods compared to Indian researchers. The results call for increased statistical training, better standards of research methodology, and more use of advanced analytical techniques in Indian LIS studies to solidify the empirical underpinnings of the discipline.