# A study of effective statistical tools for longitudinal data analysis

Author Affiliations

^{1}Department of Ag. Statistics, Applied Mathematics and Computer Science, UAS, GKVK, Bengaluru, India^{2}Department of Ag. Statistics, Applied Mathematics and Computer Science, UAS, GKVK, Bengaluru, India

*Res. J. Mathematical & Statistical Sci.,* **Volume 6, Issue (6),** Pages 1-5, June,12 **(2018)**

## Abstract

Longitudinal studies play a very important role in human life, plant science and social sciences. In such studies, data are collected from the respondents over a period of time or periodical intervals. Consequently, observations are correlated and effective statistical methods/techniques are required for the analysis of such data. Other names given to such studies are the analysis of repeated measurements and growth curves. The main focus of such data analysis is to study the changes caused by development, aging and other factors such as application of different treatments over a period of time. Such studies typically have unbalanced designs, missing data and time varying covariates and thus not tenable to standard statistical methods. This paper gives an overview of literature and important references which lead for further effective studies.

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