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The values you use vary depending upon the font size and size of the text box. Each font has different kerning characteristics, which enters into the value you end up using.

Alleyne, E., 244 Allgood-Merten, B., 470, 482 Allison, D. B., 124, 125, 126, 138, 139, 161, 163, 560 Allison, M., 409 Allshouse, J. E., 127, 143 Almeida, J. C., 600, 608 Almqvist, M., 323, 335 Alp rovitch, A., 492, 509 Alpers, J. H., 107, 120 Alpert, E. J., 518, 536 Alstead, M., 228, 239 Alter, C., 272, 286, 502, 503 Altice, F. L., 234, 243 Altman, A., 464 Altman, D. G., 6, 23, 155, 162 Alvarez, W., 32, 47 Alverez, J. H., 400, 411 Amaateau, L. M., 60, 70 Amaral-Melendez, M., 604, 608 Amble, P., 153, 164 Amick, T. L., 346, 357 Amico, E., 154, 164, 264 Aminian, S., 140 Amiri, M. M., 85, 90 Amit, Z., 152, 167 Amorosa, L., 207, 215 Amsterdam, J., 197, 217 An, Z., 215 Anagnostopoulos, F., 54, 68 Anand, S. A., 606, 608 Anand, V. K., 606, 608 Anbar, R. D., 447, 462 Ancoli-Israel, S., 326, 334 Anda, R., 346, 347, 357 Andersen, B., 83, 87, 267, 278, 287, 290, 502, 503 Andersen, R., 144, 231, 239 Andersen, T., 144 Anderson, B., 502, 503 Anderson, B. J., 200, 210, 211, 212, 213, 214, 217, 288 Anderson, B. L., 274, 278, 287, 515, 529, 537 Anderson, C., 450, 458 Anderson, D. A., 125, 144 Anderson, D. M., 155, 164 Anderson, E. A., 195, 216 Anderson, H. V., 363 Anderson, J., 361 Anderson, J. J., 171, 185 Anderson, J. L., 357 Anderson, J. R., 155, 165 Anderson, J. S., 380, 381, 384 Anderson, J. W., 141 Anderson, K. E., 140

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particular continuous variable over time However, qualitative development can also be examined by modeling how individuals pass through qualitatively different stages over time Examples of stage sequences are abundant in psychology These include Piaget s (1973) stage model of cognitive development, Freud s (1961) stages of psychosocial development, Kohlberg s (1966) stage sequence of moral development, and Erikson s (1950) stages of ego identity Following from our examination of adolescent depression, we might be interested in stability and change in depression throughout adolescence In the following discussion we extend this previous latent class analysis by modeling transitions between different latent classes of depression over time Latent Markov Models Latent Markov modeling is a framework for examining stability and change in a categorical latent variable measured by categorical variables repeatedly over time in the same sample of individuals (Langeheine, 1994; van de Pol & Langeheine, 1990).

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The button s OnAction property is set to a procedure named ChangeNumFormat, which follows. This procedure displays the Number tab of Excel s Format Cells dialog box (see Figure 22-13).

Latent Markov models assume that time is a discrete process, rather than a continuous one, and summarize change over time by estimating transitions from one time point to the next Traditional Markov models involve a single indicator of class membership measured at multiple times, in which the conditional response probabilities are constrained to be equal over time in order to achieve identi cation A multiple indicator Markov model measures class membership at each time using a set of two or more items In this model the conditional response probabilities do not need to be constrained to be equal over time in order to achieve identi cation, although this constraint helps interpretability The multiple indicator latent Markov model (Langeheine, 1994; Langeheine & van de Pol, 1994; Macready & Dayton, 1994) is identical to the latent transition analysis framework (Collins & Wugalter, 1992); this longitudinal approach is presented in the following discussion.

To find out specific details about an event, consult the online help. The help system also lists the events available for each control.

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Latent Transition Analysis Latent class theory has been extended to a longitudinal framework allowing modeling of change in a discrete latent variable This framework, called latent transition analysis (LTA; Collins et al, 1997; Collins & Wugalter, 1992; Hyatt & Collins, 2000), provides a way of estimating and testing models of stage-sequential development in longitudinal data In LTA, change is measured using multiple manifest indicators This approach allows researchers to estimate the prevalence of stages (ie, latent classes) and the incidence of transitions to different stages over time for multiple groups In the.

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