IntroductionThe debate over the use of appropriate statistical analyzes for behavioral data is far from new, with various publications citing theories dating back to around 1874 by the famous statistician Sir Francis Galton.1 However , has predictably evolved over the centuries and is now an interesting topic in the field of psychiatric medicine in the analysis of psychiatric rating scale data. Parametric statistical tests are the main methods used to analyze psychiatric rating scale data, however this is considered methodologically flawed.2 The problem lies, as one may already assume, that running inappropriate statistics will discredit and invalidate the data at your fingertips. , making the search impractical. With the simultaneous expansion of drug therapy and psychiatric research, it is now more critical than ever to determine the most pragmatic standardized approach for analyzing this type of data. Drawing on currently available literature, this article will discuss the topic of levels of measurement for psychiatric rating scale data, the implications of inappropriate statistical use, and the best statistical approach for analyses. Discussion Psychiatric rating scales are useful for evaluating and determining descriptions of psychiatric disorders, diagnostic severity and change with respect to therapeutic interventions, i.e. the effectiveness of treatment, in clinical practice and especially in research. Just as with general medical research, psychiatric data must be evaluated using statistical analyses. This requires that psychiatric rating scale data be classified into the appropriate measurement scales to be evaluated using appropriate statistical analyses. The three observational measurement scales... half of the paper... the conclusions of this study being an open-label study and using a new statistical model, provide some evidence, especially in the topic of smaller sample sizes (studies n < 40 ), that statistically significant evidence cannot be altered by the choice of statistical analysis. Works Cited1. Baggaley, et al. The effect of nonlinear transformations on Likert scales. Evaluation and Health Professions. 6 (1983)4:483-491.2. Forrest et al. Statistics in Medicine: ordinal scale and statistics in medical research. Brit Med J 1986 (292):537-538.3. Bandelow et al. The use of parametric and nonparametric tests in the statistical evaluation of rating scales. Pharmacopsychiatry. 31(1998):222-224.4. Delucchi, et al. Methods for analyzing skewed data distributions in psychiatric clinical trials: Working with many zero values. I'm J Psychiatry. 2004 (161):1159-1168.