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the Pearson product moment correlation coefficient (PPMC) has been used to quantify both (p 393), and stability and reliability were considered synonyms in representing longitudinal consistency of a set of observed scores Schutz further claimed that recent developments, mainly in the use of structural equation modeling, provide a sound basis for the estimation of stability and reliability He outlined the source of error associated with reliability measures and concluded that the traditional methods tend to underestimate the reliability of the measured trait by ignoring the distinction between random measurement errors and systematic error variance When a stable measure is administered to persons twice or more over a period of time, variability over repeated measurements may be attributed to its inherent lack of measurement reliability (ie, random error associated with the manifest variable, and a systematic error associated with the time lapse).

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McKim, W. A. (1991). Drugs and behavior: An introduction to behavioral pharmacology (2nd ed.). Englewood Cliffs, NJ: Prentice-Hall. McLeod, J. D., Kessler, R. C., & Landis, K. R. (1992). Speed of recovery from major depressive episodes in a community sample of married men and women. Journal of Abnormal Psychology, 101, 277 286. McNally, R. J. (2001). The cognitive psychology of repressed and recovered memories of childhood sexual abuse: Clinical implications. Psychiatric Annals, 31, 509 514. McNeill, B. W., May, R. J., & Lee, V. E. (1987). Perceptions of counselor source characteristics by premature and successful terminators. Journal of Counseling Psychology, 34, 86 89. McReynolds, P. (1987). Lightner Witmer: Littleknown founder of clinical psychology. American Psychologist, 42, 849 858. Meehl, P. E. (1954). Clinical versus statistical prediction. Minneapolis: University of Minnesota Press. Meehl, P. E. (1962). Schizotaxia, schizotypy, schizophrenia. American Psychologist, 17, 827 838. Meehl, P. E. (1965). Seer over sign: The first good example. Journal of Experimental Research in Personality, 1, 27 32. Meehl, P. E. (1997). Credentialed persons, credentialed knowledge. Clinical Psychology: Science and Practice, 4, 91 98. Megargee, E. J. (1990). A guide to obtaining a psychology internship. Muncie, IN: Accelerated Development. Meichenbaum, D. H. (1977). Cognitive-behavior modification. New York: Plenum Press. Mercado, A. C., Carroll, L. J., Cassidy, J. D., & Cote, P. (2000). Coping with neck and low back pain in the general population. Health Psychology, 19, 333 338. Mercer, D. E., & Woody, G. E. (1998). An individual drug counseling approach to treat cocaine addiction: The collaborative cocaine treatment study model. Washington, DC: National Institute on Drug Abuse. Mercer, J. R., & Lewis, J. F. (1979). System of Multicultural Pluralistic Assessment. Cleveland, OH: Psychological Corporation.

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and RATING = High. Therefore, the estimated logit equals g(x) = 0.5478 0.0423(4) 0.0107(135) + 0.9476(2) = 0.2663 e 0.2663 = 0.43382 1 + e 0.2663 Therefore, the estimated probability equals about 43.4% that a cereal with 4 grams of protein, 135 milligrams of sodium, and 2 grams of ber is of high nutritional value. Note that WEKA reports this same probability (except for slight rounding variations) for the rst instance in Table 4.31. It follows that the model estimates a probability equal to 1 (x) = 56.6% that this cereal has a low nutritional rating. Therefore, based on the higher probability, the model incorrectly classi ed the record as Low. Table 4.31 also shows reports the odds ratios for the three continuous predictors. (x) = For example, the odds ratio for PROTEIN is OR = eb1 = e 0.0423 = 0.9586. This is interpreted as the odds of a cereal with x + 1 grams of protein being of high nutritional value compared to a cereal with x grams of protein being highly nutritious.

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In this case, once the researcher secures the inherent reliability of the measurement tool (ie, testretest, internal consistency, split-half ), the variance error associated with instability can be attributed to the changes that occurred between the two periods of time the measure was administered Schutz (1998) claimed that the structural equation modeling method allows the quantification of the temporal stability of the error variances by separating out the systematic and random components of error variance This structural equation modeling concept, however, may not be applicable in estimating stability of introspective reports due to the fact that it relies on multiple indicators for measuring a construct In the current chapter, we propose a method to estimate the temporal stability of introspective measures, where a single indicator for each one of two time points for each person is sufficient.

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