Results 231 to 240 of about 1,083,143 (283)

Latent profile analysis and influencing factors of engagement in medication safety among older adults with cardiometabolic multimorbidity: a cross-sectional study. [PDF]

BMJ Open
Liu C, Chen J, Jin R, Li J, Cui M, Wang F, Chen L.   +6 more
europepmc   +1 more source

Uncovering Latent Structures of School Belonging, Emotional Problems, Psychological Symptoms, Meaningful School, and Ostracism: A Latent Profile Analysis. [PDF]

Brain Behav
Doğrusever C, Kurtuluş HY, Kaya A, Türk N, Yıldırım M.   +4 more
europepmc   +1 more source

Job-search self-efficacy in unemployed individuals with mental health issues: investigating the role of self-stigma with variable-centered and person-centered approaches. [PDF]

BMC Psychol
Schlachter S, Gantner M, Gralla M, Pumptow M, Adam SH, Erschens R, Gündel H, von Wietersheim J, Rüsch N.   +8 more
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Academic burnout profiles and their correlates: a latent profile analysis of Chinese university students. [PDF]

Front Psychol
Li Y, Li Y, Ye X, Yan S.
europepmc   +1 more source

Estimating the baseline age when longitudinal changes in biomarkers accelerate: application to an imaging study of preclinical Alzheimer disease. [PDF]

BMC Med Res Methodol
Xiong C, Agboola F, Luo J.
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Profiles of psychopathology and quality of life in individuals with recent displacement experiences: a latent profile analysis. [PDF]

BMC Public Health
Amiri MA, Andersson G, Vernmark K, Leiler A, Bjärtå A.   +4 more
europepmc   +1 more source

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On Profile Likelihood

Journal of the American Statistical Association, 2000
Abstract We show that semiparametric profile likelihoods, where the nuisance parameter has been profiled out, behave like ordinary likelihoods in that they have a quadratic expansion. In this expansion the score function and the Fisher information are replaced by the efficient score function and efficient Fisher information.
Murphy, S.A., van der Vaart, A.W.
openaire   +2 more sources

Adjustments to profile likelihood

Biometrika, 1989
Summary: Conditional and marginal likelihoods constructed from parameter-dependent functions of the data have an additional parameter dependence that changes with the choice of supporting metric for the corresponding densities. We consider constructing marginal and conditional likelihoods by using densities expressed in terms of an intrinsic choice of ...
Fraser, D. A. S., Reid, N.
openaire   +1 more source

An explanation of generalized profile likelihoods

Statistics and Computing, 2001
Let X, T, Y be random vectors such that the distribution of Y conditional on covariates partitioned into the vectors X e x and T e t is given by f(ys x, p), where p e (t, η(t)). Here t is a parameter vector and η(t) is a smooth, real–valued function of t. The joint distribution of X and T is assumed to be independent of t and η.
Joan G. Staniswalis, Peter F. Thall
openaire   +1 more source