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M Cover, P G cs, and R M Gray Kolmogorov s contributions to infora mation theory and algorithmic complexity Ann Prob, pages 840 865, July 1989 [115] T M Cover, A A El Gamal, and M Salehi Multiple access channels with arbitrarily correlated sources IEEE Trans Inf Theory, pages 648 657, Nov 1980 [116] T M Cover and P E Hart Nearest neighbor pattern classi cation IEEE Trans Inf Theory, pages 21 27, Jan 1967 [117] T M Cover and S Pombra Gaussian feedback capacity IEEE Trans Inf Theory, pages 37 43, January 1989 [118] T M Cover and J A Thomas Determinant inequalities via information theory SIAM J Matrix Anal and Its Applications, 9(3):384 392, July 1988 [119] T M Cover Broadcast channels IEEE Trans Inf Theory, IT-18:2 14, 1972 [120] T M Cover Enumerative source encoding IEEE Trans Inf Theory, IT19(1):73 77, Jan 1973 [121] T M.

This work helped bridge the gap between psychiatry and the other medical specialties, laying the foundation for the development of psychosomatic medicine and liaison psychiatry (Lipsitt, 1999)..

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When assessing whether different types of care reduce inpatient length of stay, Foster (1998) started the clock when patients were rst admitted to the hospital, but when assessing whether aftercare services reduce inpatient readmissions, Foster (1999) started the clock when patients were rst released The choice of precipitating event varies widely across research questions Some options include entry into a particular level of schooling (Rayman & Brett, 1995; Roderick, 1994), release from jail (Henning & Frueh, 1996), divorce or separation (Wu, 1995), or report of child maltreatment (Fryer & Miyoshi, 1994) Consideration of the process under study usually leads to a defensible decision When it does not, an arbitrary time can be used as long as that time is itself unrelated to event occurrence Researchers conducting randomized clinical trials, for example, typically use the date of randomization or intervention (Hurlburt et al, 1996; Greenhouse, Stangl, Kupfer, & Prien, 1991).

relatively pure factor markers, that is, traits assigned to the 10 diagonal (I I to V V ) cells of the table If simple structure would in fact materialize, most if not all of the variables would be found in those cells If, on the other hand, the empirical structure is essentially circumplex, only 111% of the variables would nd their way to the diagonal cells In Hendriks s (1997) analysis of 914 items, 105 (115%) ended up in those cells That illustration is as dramatic as is the percentage of variables that would have to be discarded in a proper application of the simple-structure model In the discussion of the person-centered approach, I introduced a distinction between the contexts of prediction and communication.

Cover An achievable rate region for the broadcast channel IEEE Trans Inf Theory, IT-21:399 404, 1975 [122] T M Cover A proof of the data compression theorem of Slepian and Wolf for ergodic sources IEEE Trans Inf Theory, IT-22:226 228, 1975 [123] T M Cover An algorithm for maximizing expected log investment return IEEE Trans Inf Theory, IT-30(2):369 373, 1984 [124] T M Cover Kolmogorov complexity, data compression and inference In J Skwirzynski (Ed), The Impact of Processing Techniques on Communications, Vol 91 of Applied Sciences Martinus-Nijhoff, Dordrecht, The Netherlands, 1985..

But beware of the measurement imprecision created when the chosen precipitating event only approximates the conceptual beginning of time When modeling illnesses, for example, the conceptual beginning of time is the onset of the illness episode, yet medical researchers often use the date of evaluation or diagnosis Because the time between onset and entry into treatment can vary greatly across individuals (Monroe, Simons, & Thase, 1991) and the magnitude of this lag time may be an important predictor of a treatment s ef cacy, use of these more easily measured dates may actually add even more errors into the de nition of event occurrence What happens if the start date is unknown for some individuals under study Statisticians say that such observations are left censored (to distinguish them from right-censored observations in which the event times are unknown).

Against that background, it should be noted that the predictive gain of the off-diagonal AB5C facets over the ve principal components is nil, as the facets are linear combinations of the components However, they do serve conceptual, interpretive, and communicative purposes An individual s pro le of scores on the FFPI, for example, may be typi ed by that person s single most characteristic facet; thus, for example, a person whose highest score is on factor V and whose second highest score is on III may be characterized by the cluster of expressions and adjectives that form the V III facet (Knows what he/she is talking about, Uses his/her brains, Sees through problems, and the many other items listed by Hendriks, 1997, for this Tight Intelligence facet).

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