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Applied Logistic Regression

TL;DR: Hosmer and Lemeshow as discussed by the authors provide an accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets.
Abstract: From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models... Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references."- Choice "Well written, clearly organized, and comprehensive... the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." - Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical."-The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.
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Journal ArticleDOI
TL;DR: Eating disorders, although relatively uncommon, represent a public health concern because they are frequently associated with other psychopathology and role impairment, and are frequently under-treated.

4,304 citations

Journal ArticleDOI
TL;DR: A recent survey of capture-recapture models can be found in this article, with an emphasis on flexibility in modeling, model selection, and the analysis of multiple data sets.
Abstract: The understanding of the dynamics of animal populations and of related ecological and evolutionary issues frequently depends on a direct analysis of life history parameters. For instance, examination of trade-offs between reproduction and survival usually rely on individually marked animals, for which the exact time of death is most often unknown, because marked individuals cannot be followed closely through time. Thus, the quantitative analysis of survival studies and experiments must be based on capture- recapture (or resighting) models which consider, besides the parameters of primary interest, recapture or resighting rates that are nuisance parameters. Capture-recapture models oriented to estimation of survival rates are the result of a recent change in emphasis from earlier approaches in which population size was the most important parameter, survival rates having been first introduced as nuisance parameters. This emphasis on survival rates in capture-recapture models developed rapidly in the 1980s and used as a basic structure the Cormack-Jolly-Seber survival model applied to an homogeneous group of animals, with various kinds of constraints on the model parameters. These approaches are conditional on first captures; hence they do not attempt to model the initial capture of unmarked animals as functions of population abundance in addition to survival and capture probabilities. This paper synthesizes, using a common framework, these recent developments together with new ones, with an emphasis on flexibility in modeling, model selection, and the analysis of multiple data sets. The effects on survival and capture rates of time, age, and categorical variables characterizing the individuals (e.g., sex) can be considered, as well as interactions between such effects. This "analysis of variance" philosophy emphasizes the structure of the survival and capture process rather than the technical characteristics of any particular model. The flexible array of models encompassed in this synthesis uses a common notation. As a result of the great level of flexibility and relevance achieved, the focus is changed from fitting a particular model to model building and model selection. The following procedure is recommended: (1) start from a global model compatible with the biology of the species studied and with the design of the study, and assess its fit; (2) select a more parsimonious model using Akaike's Information Criterion to limit the number of formal tests; (3) test for the most important biological questions by comparing this model with neighboring ones using likelihood ratio tests; and (4) obtain maximum likelihood estimates of model parameters with estimates of precision. Computer software is critical, as few of the models now available have parameter estimators that are in closed form. A comprehensive table of existing computer software is provided. We used RELEASE for data summary and goodness-of-fit tests and SURGE for iterative model fitting and the computation of likelihood ratio tests. Five increasingly complex examples are given to illustrate the theory. The first, using two data sets on the European Dipper (Cinclus cinclus), tests for sex-specific parameters,

4,038 citations

01 Jan 2010
TL;DR: This paper synthesizes, using a common framework, recent developments of capture-recapture models oriented to estimation of survival rates together with new ones, with an emphasis on flexibility in modeling, model selection, and the analysis of multiple data sets.

4,011 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the developmental process of nascent entrepreneurs for 18 months and found that bridging and bonding social capital, consisting of both strong and weak ties, was a robust predictor for nascent entrepreneurs and advancing through the start-up process.

3,777 citations

Journal ArticleDOI
07 Jun 2006-JAMA
TL;DR: Basal-like breast tumors occurred at a higher prevalence among premenopausal African American patients compared with postmenopausal American and non-African American patients in this population-based study, and their associations with tumor size, axillary nodal status, mitotic index, nuclear pleomorphism, combined grade, p53 mutation status, and breast cancer-specific survival were examined.
Abstract: ContextGene expression analysis has identified several breast cancer subtypes, including basal-like, human epidermal growth factor receptor-2 positive/estrogen receptor negative (HER2+/ER–), luminal A, and luminal B.ObjectivesTo determine population-based distributions and clinical associations for breast cancer subtypes.Design, Setting, and ParticipantsImmunohistochemical surrogates for each subtype were applied to 496 incident cases of invasive breast cancer from the Carolina Breast Cancer Study (ascertained between May 1993 and December 1996), a population-based, case-control study that oversampled premenopausal and African American women. Subtype definitions were as follows: luminal A (ER+ and/or progesterone receptor positive [PR+], HER2−), luminal B (ER+ and/or PR+, HER2+), basal-like (ER−, PR−, HER2−, cytokeratin 5/6 positive, and/or HER1+), HER2+/ER− (ER−, PR−, and HER2+), and unclassified (negative for all 5 markers).Main Outcome MeasuresWe examined the prevalence of breast cancer subtypes within racial and menopausal subsets and determined their associations with tumor size, axillary nodal status, mitotic index, nuclear pleomorphism, combined grade, p53 mutation status, and breast cancer–specific survival.ResultsThe basal-like breast cancer subtype was more prevalent among premenopausal African American women (39%) compared with postmenopausal African American women (14%) and non–African American women (16%) of any age (P<.001), whereas the luminal A subtype was less prevalent (36% vs 59% and 54%, respectively). The HER2+/ER− subtype did not vary with race or menopausal status (6%-9%). Compared with luminal A, basal-like tumors had more TP53 mutations (44% vs 15%, P<.001), higher mitotic index (odds ratio [OR], 11.0; 95% confidence interval [CI], 5.6-21.7), more marked nuclear pleomorphism (OR, 9.7; 95% CI, 5.3-18.0), and higher combined grade (OR, 8.3; 95% CI, 4.4-15.6). Breast cancer–specific survival differed by subtype (P<.001), with shortest survival among HER2+/ER− and basal-like subtypes.ConclusionsBasal-like breast tumors occurred at a higher prevalence among premenopausal African American patients compared with postmenopausal African American and non–African American patients in this population-based study. A higher prevalence of basal-like breast tumors and a lower prevalence of luminal A tumors could contribute to the poor prognosis of young African American women with breast cancer.

3,634 citations