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[null,"1.","Record Nr.",null,"UNINA9910791707803321"]
[null,null,"Autore",null,"Wang Jichuan"]
[null,null,"Titolo",null,"Structural equation modeling [[electronic resource] ] : applications using Mplus / / Jichuan Wang, Xiaoqian Wang"]
[null,null,"Pubbl/distr/stampa",null,"Chichester, West Sussex, : Wiley, 2012"]
[null,null,"ISBN",null,"1-283-55059-8"]
[{"$nulls":4},"9786613863041"]
[{"$nulls":4},"1-118-35629-2"]
[{"$nulls":4},"1-118-35625-X"]
[{"$nulls":4},"1-118-35631-4"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (479 p.)"]
[null,null,"Collana",null,"Wiley series in probability and statistics"]
[null,null,"Classificazione",null,"SOC027000"]
[null,null,"Disciplina",null,"519.5/3"]
[null,null,"Soggetti",null,"Multivariate analysis - Data processing"]
[{"$nulls":4},"Social sciences - Statistical methods - Data processing"]
[{"$nulls":4},"Structural equation modeling - Data processing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Structural Equation Modeling: Applications Using Mplus; Contents; Preface; 1 Introduction; 1.1 Model formulation; 1.1.1 Measurement model; 1.1.2 Structural model; 1.1.3 Model formulation in equations; 1.2 Model identification; 1.3 Model estimation; 1.4 Model evaluation; 1.5 Model modification; 1.6 Computer programs for SEM; Appendix 1.A Expressing variances and covariances among observed variables as functions of model parameters; Appendix 1.B Maximum likelihood function for SEM; 2 Confirmatory factor analysis; 2.1 Basics of CFA model; 2.2 CFA model with continuous indicators"]
[{"$nulls":4},"2.3 CFA model with non-normal and censored continuous indicators2.3.1 Testing non-normality; 2.3.2 CFA model with non-normal indicators; 2.3.3 CFA model with censored data; 2.4 CFA model with categorical indicators; 2.4.1 CFA model with binary indicators; 2.4.2 CFA model with ordered categorical indicators; 2.5 Higher order CFA model; Appendix 2.A BSI-18 instrument; Appendix 2.B Item reliability; Appendix 2.C Cronbach's alpha coefficient; Appendix 2.D Calculating probabilities using PROBIT regression coefficients; 3 Structural equations with latent variables; 3.1 MIMIC model"]
[{"$nulls":4},"3.2 Structural equation model3.3 Correcting for measurement errors in single indicator variables; 3.4 Testing interactions involving latent "]
[{"$nulls":4},"variables; Appendix 3.A Influence of measurement errors; 4 Latent growth models for longitudinal data analysis; 4.1 Linear LGM; 4.2 Nonlinear LGM; 4.3 Multi-process LGM; 4.4 Two-part LGM; 4.5 LGM with categorical outcomes; 5 Multi-group modeling; 5.1 Multi-group CFA model; 5.1.1 Multi-group first-order CFA; 5.1.2 Multi-group second-order CFA; 5.2 Multi-group SEM model; 5.3 Multi-group LGM; 6 Mixture modeling; 6.1 LCA model; 6.1.1 Example of LCA"]
[{"$nulls":4},"6.1.2 Example of LCA model with covariates6.2 LTA model; 6.2.1 Example of LTA; 6.3 Growth mixture model; 6.3.1 Example of GMM; 6.4 Factor mixture model; Appendix 6.A Including covariate in the LTA model; 7 Sample size for structural equation modeling; 7.1 The rules of thumb for sample size needed for SEM; 7.2 Satorra and Saris's method for sample size estimation; 7.2.1 Application of Satorra and Saris's method to CFA model; 7.2.2 Application of Satorra and Saris's method to LGM; 7.3 Monte Carlo simulation for sample size estimation; 7.3.1 Application of Monte Carlo simulation to CFA model"]
[{"$nulls":4},"7.3.2 Application of Monte Carlo simulation to LGM7.3.3 Application of Monte Carlo simulation to LGM with covariate; 7.3.4 Application of Monte Carlo simulation to LGM with missing values; 7.4 Estimate sample size for SEM based on model fit indices; 7.4.1 Application of MacCallum, Browne and Sugawara's method; 7.4.2 Application of Kim's method; References; Index; Series"]
[null,null,null,"Sommario/riassunto","A reference guide for applications of SEM using Mplus  Structural Equation Modeling: Applications Using Mplus is intended as both a teaching resource and a reference guide. Written in non-mathematical terms, this book focuses on the conceptual and practical aspects of Structural Equation Modeling (SEM). Basic concepts and examples of various SEM models are demonstrated along with recently developed advanced methods, such as mixture modeling and model-based power analysis and sample size estimate for SEM. The statistical modeling program, Mplus, is also featu"]
[null,"2.","Record Nr.",null,"UNINA9910346752303321"]
[null,null,"Autore",null,"Rudolf Hoermann"]
[null,null,"Titolo",null,"Homeostasis and Allostasis of Thyroid Function"]
[null,null,"Pubbl/distr/stampa",null,"Frontiers Media SA, 2018"]
[null,null,"Descrizione fisica",null,"1 online resource (107 p.)"]
[null,null,"Collana",null,"Frontiers Research Topics"]
[null,null,"Soggetti",null,"Medicine and Nursing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","The discovery of the negative feedback of thyroid hormones on pituitary thyroid-stimulating hormone (TSH) secretion, a classical endocrine feedback control system, has shaped diagnosis and treatment of thyroid disease for the last decades. Based on this concept, a unique diagnostic category of subclinical thyroid disorders was introduced, being defined exclusively by an abnormal TSH response in the presence of thyroid hormone concentrations within the reference range. Although this approach was able to deliver a conceptually straightforward disease definition problems surfaced in clinical practice as neither the diagnostic reference range nor the appropriate threshold for initiating substitution treatment are universally agreed upon for subclinical thyroid disorders. The situation is further aggravated by the so-called syndrome T, which comprises a substantial but heterogeneous group of L-T4 treated patients with hypothyroidism with reduced quality of life despite \"normal\" TSH values.</p><p>A limited understanding of the physiological relationships between TSH and thyroid hormones may be a main reason for clinical difficulties in dealing with the causes of syndrome T and tailoring substitution therapy for hypothyroid patients with subclinical thyroid disorders. </p><p>Feedback regulation has recently been shown to be much more complex than previously assumed. The concept of homeostatic control has also been extended to include the lesser known but equally important allostatic thyroid regulation.The latter aims at adaptive homeostasis or stability through changing setpoints and modulating structural parameters of feedback control, as may be appropriate to adapt to a vast array of conditions spanning "]
[{"$nulls":4},"from fetal life, aging, pregnancy, exercise, starvation, obesity, psychiatric disorders to the severe non-thyroidal illness syndrome.</p><p>A better understanding of homeostatic and allostatic mechanisms, which govern the behaviour of pituitary-thyroid feedback control, is on the horizon. This promises to improve the diagnostic utility of laboratory methods, laying the foundation for personalised methods to optimise dosage and modality of substitution therapy. The emerging new world of thyroid physiology is reflected on the side of clinical medicine in a new, relational paradigm for diagnosis and treatment.</p><p>Considerable progress has been made in this respect in the following key areas:</p><p>• the significance of complementary information processing structures within the feedback loop, in particular ultrashort feedback of TSH on its own secretion and the action of a TSH-T3 shunt unburdening the thyroid from T4 synthesis in imminent thyroid failure,</p><p>• the unravelling of spatio-temporal dynamics of hormone concentrations ranging from ultradian to circannual rhythms and including hysteresis effects,</p><p>• the emergence of \"non-canonical\" mechanisms of thyroid hormone signalling beyond transcriptional control of gene expression,</p><p>• the physiological actions of thyronine metabolites, which have been previously regarded as biologically inactive, such as thyronamines and iodothyroacetates,</p><p>• the characterisation of distinct patterns in the adaptive processes to stress and strain and their conclusive explanation through reactions to type 1 and type 2 allostatic load.</p><p>This collective volume contains the contributions to the Research Topic \"Homeostasis and Allostasis of Thyroid Function\", which was originally published by the journal Frontiers in Endocrinology. Authored by an international team of experts from three continents ,the book provides a comprehensive overview on thyroid control from recent research in basic, computational and clinical thyroidology. Many aspects addressed here can be expected to stimulate future research. A more comprehensive view and better integration of in-vitro, in-silico and in-vivo investigations will be invaluable in paving the way to this new world of thyroidology."]