Suesse Thomas (8 results)

Taschenbuch. Condition: Neu. Analysis & Diagnostics of Categorical Variables with Multiple Outcomes | Odds Ratio Estimation, Modelling Strategies, Deletion Diagnostics and Graphical Diagnostic Methods for Multiple Response Data | Thomas Suesse | Taschenbuch | 224 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783838310671 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

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Condition: New. Editor(s): Susse, Roland. Num Pages: 700 pages. . . 2005. Hardcover. . . . .

Condition: New. Editor(s): Susse, Roland. Num Pages: 700 pages. . . 2005. Hardcover. . . . . Books ship from the US and Ireland.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Surveys often contain qualitative variables for which respondents may select any number of the outcome categories. For instance, for the question 'What type of contraceptive have you used ' with possible responses (oral, condom, lubricated condom, spermicide, and diaphragm), respondents would be instructed to select as many of the J = 5 outcomes as apply. This situation is known as multiple responses and outcomes are referred to as items. This thesis discusses several approaches to analysing such data. First, for stratified multiple response data, we consider three ways of defining the common odds ratio a summarising measure for the conditional association between a row variable and the multiple response variable, given a stratification variable. We derive several new dually consistent log-odds ratio and (co)variance estimators. Next we focus on deletion diagnostics for multiple response data models, e.g. logistic regression, and compare deletion strategies. Then modelling strategies for repeated multiple response data are investigated. Last, we consider a graphical diagnostic method to detect a mis-specification of a covariate of the proportional odds model. 224 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Suesse ThomasIn 2009, Thomas Suesse received his PhD degree in statistics from theVictoria University of Wellington, New Zealand.Recently he joined the University of Wollongong, Australia, as a research fellow. His main research intere.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Surveys often contain qualitative variables for which respondents may select any number of the outcome categories. For instance, for the question 'What type of contraceptive have you used ' with possible responses (oral, condom, lubricated condom, spermicide, and diaphragm), respondents would be instructed to select as many of the J = 5 outcomes as apply. This situation is known as multiple responses and outcomes are referred to as items. This thesis discusses several approaches to analysing such data. First, for stratified multiple response data, we consider three ways of defining the common odds ratio a summarising measure for the conditional association between a row variable and the multiple response variable, given a stratification variable. We derive several new dually consistent log-odds ratio and (co)variance estimators. Next we focus on deletion diagnostics for multiple response data models, e.g. logistic regression, and compare deletion strategies. Then modelling strategies for repeated multiple response data are investigated. Last, we consider a graphical diagnostic method to detect a mis-specification of a covariate of the proportional odds model.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 224 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Surveys often contain qualitative variables for which respondents may select any number of the outcome categories. For instance, for the question 'What type of contraceptive have you used ' with possible responses (oral, condom, lubricated condom, spermicide, and diaphragm), respondents would be instructed to select as many of the J = 5 outcomes as apply. This situation is known as multiple responses and outcomes are referred to as items. This thesis discusses several approaches to analysing such data. First, for stratified multiple response data, we consider three ways of defining the common odds ratio a summarising measure for the conditional association between a row variable and the multiple response variable, given a stratification variable. We derive several new dually consistent log-odds ratio and (co)variance estimators. Next we focus on deletion diagnostics for multiple response data models, e.g. logistic regression, and compare deletion strategies. Then modelling strategies for repeated multiple response data are investigated. Last, we consider a graphical diagnostic method to detect a mis-specification of a covariate of the proportional odds model.