Introduction
The debate on the use of appropriate statistical analyses for behavioral data is far from new, with various literature quoting theories dating back to around 1874 by the famous statistician Sir Francis Galton.1 It has however, foreseeably evolved through the ages and is now a compelling topic in the field of psychiatric medicine in the analysis of psychiatric rating scale data. Parametric statistical tests are the major methods used to analyze psychiatric rating scale data, however this is majorly viewed as methodologically incorrect.2 The issue lies, as one may already assume, in the fact that performing inappropriate statistics will discredit and invalidate the data at hand, rendering the research impractical. With the contemporary expansion of pharmacological therapy and research in the psychiatric field, now more than ever it is paramount to determine the most pragmatic standardized approach for analyzing this type of data. Based off the current available literature, this paper will discuss the argument of the levels of measurements for psychiatric rating scale data, the implications of inappropriate statistical use, and the best statistical approach for analyses.
Debate
Psychiatric rating scales are useful in assessing and determining descriptions of psychiatric disorders, diagnostic severity, and change from therapeutic interventions i.e. treatment efficacy, in clinical practice and especially in research. Just as with research of general medical practice, psychiatric data must be assessed by statistical analysis. This requires psychiatric rating scale data to be categorized in the appropriate scales of measurement to be assessed by appropriate statistical analyses. The three observational scales of measure...
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...tations of this study being an open label trial and using a new statistical model, it does provide some evidence, especially in the argument of smaller sample sizes (studies n <40), that statistically significant evidence may not be altered by choice of statistical analysis.
Works Cited
1. Baggaley, et al. The effect of nonlinear transformations on a Likert scale. 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 vs. Nonparametric Tests in the Statistical Evaluation of Rating Scales. Pharmacopsychiat. 31(1998):222-224.
4. Delucchi, et al. Methods for Analysis of Skewed Data Distributions in Psychiatric Clinical Studies: Working With Many Zero values. Am J Psychiatry. 2004 (161):1159-1168.
American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders, 5th Edition. Arlington, VA: American Psychiatric Publishing.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.
Zung, W. W. K., (1965). A self-rating depression scale. Arch. Gen. Psychiatry. 12:63-70.[Duke Univ. Med. Ctr., Dept. Psychiatry, Durham, NC]
middle of paper ... ... Retrieved June 16, 2002, from http://nimh.nih.gov/publicat/numbers.cfm. National Mental Health Association. 2000 May 15.
Bech. "Fifty Years with the Hamilton Scales for Anxiety and Depression. A Tribute to Max Hamilton." National Center for Biotechnology Information. U.S. National Library of Medicine, n.d. Web. 22 Apr. 2014.
Nelson-Gray, Rosemery O. "Treatment Utility Of Psychological Assessment." Psychological Assessment 15.4 (2003): 521-531. PsycARTICLES. Web. 12 Nov. 2013.
In this day and age anyone can write anything and put it on the internet for everyone to read. You have to be diligent in separating fact from fiction. If you are skeptical you may have to do your own research to see where the information originated. Do not believe everything you read just because it states it was from a study as it may not be reliable or truthful. Both of these studies had interesting information, however since they both were lacking sufficient data it was hard to determine if the studies were completely honest and adequate or not.
Olley, B. O., & Kola, L. (2005). The british journal of psychiatry. Community study of
The reliability and validity were researched by using three types of studies: mixed diagnostic group, certified patients diagnosed with DSM-III-R anxiety disorders and a non-clinical sample. It should be noted that the that was used population were psychiatric patients s...
Teplin, L. A., Abram, K. M., & McClelland, G. M. (1994). Does psychiatric disorder predict
McGrath, E. C., McGonagle, K.A., Zhao, S., Nelson, C.B., Hughes, M., Eshleman, S., Wittchen, H-U., & Kendler, K.S.(2007).Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: Results from the National Comorbidity Survey. Archives of General Psychiatry, 51, 3-14.
Kendell, R. and Jablensky, A. (2003), Distinguishing between the validity and utility of psychiatric diagnoses, American Journal of Psychiatry, Vol. 160, No. 1, pp. 4-12.
Simpson, C. (2007) ‘Mental Health part3: Assessment and Treatment of Depression’ British Journal of Healthcare assistants. pp 167-171.
Kessler, R., Chiu, W., Demler, O., & Walters, E. (2005, June). The Numbers Count: Mental Disorders in America. Retrieved Febuary 13, 2011, from National Institute of Mental Health: http://www.nimh.nih.gov
There are a total of 36 clients that participated in the study, 15 being men and 21 being women. All of the clients requested therapy and also the clients are over the age of 18. “Exclude from the study were clients exhibiting sings of psychotic behavior, disoriented thinking, or neurological impairment”. The mean age of the clients is 27, the range 18-42. The client “presenting problem included issues such as depression, social or performance anxiety, relationship conflicts or lack of impulse control. None of the client where ...