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Animal models of nicotine addiction, 149 153 Anxiety: cancer and, 272 273 coronary heart disease and, 604 immune function and, 80 81 movement therapies for, 604 recurrent abdominal pain and, 402 spinal cord injury and, 423 women s health and, 520 Aromatherapy, 603 Arthritis and musculoskeletal conditions, 169 185 chronic pain studies, 57 58 coping, 57, 58 diathesis, 170 176 biological factors, 170 173 depression, 174 175 bromyalgia (FM), 172 173 neuroticism, 173 osteoarthritis (OA), 171 positive affect, 175 psychological factors, 173 175 rheumatoid arthritis, 170 171 self-ef cacy and control, 173 174 social diathesis factors, 175 176 social support, 175 176 somatization, 175 stigma, 176 future directions, 184 185 osteopathy, 593 social support and, 64, 66 stress, 176 183 appraisal, 182 biological stress systems, 176 182 coping, 182 183 HPA axis, 177 178 immune system, 179 180 pain system, 180 182 psychological stress factors, 182 183 reproductive system, 178 179 SAM axis, 178 social stress factors, 183 treatment: biological/pharmacological, 183 184 implications, 183 184 psychosocial, 184 written emotional disclosure therapy, 605 women and, 518 Art therapy, 606 Asian Americans/Paci c Islanders, 547 548 Asthma, 99 14 1 adherence, 108 109, 453 alexithymia, 102 103 autonomic nervous system and in ammatory processes in stress and, 108 children and, 453 classical and operant conditioning, 100 101 cognitive and perceptual processes, 101 102 comorbid psychiatric disorders: functional status, 107 108 mood disorders, 107 panic disorder, 106 107 effects of suggestion on pulmonary function, 101 102 epidemiology, 100 family systems theory, 103 104

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females (.46 and .41, respectively). The expected proportion in the highest level of depression is also similar for males and females (.08 and .10, respectively). However, gender differences appear in the middle levels of depression. Female adolescents are twice as likely to be in the sad latent class (.24 vs. .12), whereas male adolescents are twice as likely to be in the disliked latent class (.22 vs. .10). Figure 26.4 shows the gender differences in the prevalence of depression latent classes. A formal test of gender differences in speci c parameters requires estimates of each parameter s standard error. Although standard errors are not a byproduct of the EM algorithm, several methods for obtaining estimates of the standard errors have been proposed. One method involves a

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often untenable assumptions In these designs, scores measured more than once for each participant are almost always correlated because of consistency in individual differences among cases Although some kinds of individual differences are removed by calculating variance due to subjects in the analysis, there are likely still correlations among the repeated measures When such correlations are present, the F test for the effect of treatment is too liberal, and the probability of Type I error is greater than the nominal value The relevant assumption of sphericity is violated when the variances of difference scores among pairs of levels of a repeated-measure IV are unequal That is, the variance in difference scores between two adjacent levels (eg.

Hence, the conditional probability of observing a 0 next is p(0|1n ) = 1 p(1n 0) , p(1n 0) + p(1 ) cn + 1 (14.86)

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Athletes estimated the amount of time they spent practicing during their soccer and field hockey careers and rated sport-specific practice activities and everyday activities on their relevance to performance improvement, physical effort, mental effort, and enjoyment Results for the soccer players demonstrated that at 15 years of age, total accumulated practice time could be used to distinguish between the international and provincial players, and between all three groups by 18 years of age For the field hockey players, accumulated practice time could be used to distinguish between the international and provincial players from age 25 on, and between all three groups by age 27.

, a1 and a2) is likely to differ from the variance in difference scores between, say, a1 and a5 when the IV is something like time because scores taken at adjacent periods in time are apt to be more like each other (lower difference scores) than are scores taken farther apart in time There is some confusion in the literature regarding assumptions of sphericity, additivity, and compound symmetry (the combination of the assumption of homogeneity of variance and the assumption of homogeneity of covariance) Often these are discussed as if they are more or less interchangeable Table 51 describes differences among them in greater detail (and a yet more extended discussion is available in Tabachnick & Fidell, 2001a) Additivity is the absence of a true treatment (A) by participant (S) interaction (ie.

We have the following inequality: Lemma 2.10.1 If X and X are i.i.d. with entropy H (X), Pr(X = X ) 2 H (X) , with equality if and only if X has a uniform distribution. Proof: Suppose that X p(x). By Jensen s inequality, we have 2E log p(X) E2log p(X) , which implies that 2 H (X) = 2 Corollary X. Then

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