Indian Statistical Institute, Indian Institute of Social Welfare and Business Management, Indian Ports Association, India
Review Article
Improving linearity in health science Investigations
Author(s): Satyendra Nath Chakrabartty*
Correlation and linear regression are frequently used to evaluate the degree of
linear association between two variables and also to find the empirical relationship.
However, violations of assumptions often give results which are not valid. High value
of correlation coefficient is taken as degree of linearity between two variables and
attempt is made to fit linear regression equation. However, linearity implies high
correlation but the converse is not true. The paper describes with examples that
concept of linearity is different from correlations, effect of violation of assumptions
of correlations and linear regressions and suggests procedures to improve correlation
between two variables which can be extended to multi variables.
Keywords
Linearity; Correlation coefficient; Standard error; Normal distribution;
Generalized inverse .. View More»
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