Toxaemic signs, the presence or absence of hypertension and protein urea, are noted for women classified by social class and smoking habit. The data were collected in Bradford and contributed as a discussion problem f...
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Toxaemic signs, the presence or absence of hypertension and protein urea, are noted for women classified by social class and smoking habit. The data were collected in Bradford and contributed as a discussion problem for a one-day meeting on log-linear models held at Imperial College. Analysis using log-linear model methodology is presented as a case study.
UptonG. J. G. (1981) log-linear models, screening and regional industrial surveys,Reg. Studies15,33–45. This paper uses hierarchical log-linear models to analyse a set of cross-classified categorical data obtained fr...
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UptonG. J. G. (1981) log-linear models, screening and regional industrial surveys,Reg. Studies15,33–45. This paper uses hierarchical log-linear models to analyse a set of cross-classified categorical data obtained from a recent regional industrial survey of Northern Ireland. The data constitute a complete 27table. Selection of an appropriate model is facilitated by use of the screening technique advocated byBrown(1976). In the analysis a clear distinction is drawn between factors and responses, and attention is concentrated on locating the factor-response interactions of likely significance. The paper is intended as a companion to that ofWrigley(1980) who performs a logit analysis of the same ***. J. G. (1981) Modèles à l'échelle logarithmique linéaire procédures de sélection et enquêtes industrialo-régionales,Reg. Studies15,33–45. A partir des modèles à l'échelle logarithmique linéaire hiérarchiques, cet article cherche à analyser un ensemble de données, rédigées par tris cloisés et provenant d'une enquête industrialo-régionale récente de l'Irlande du Nord. Les données comportent un tableau 27complet. Le choix d'un modèle qui convient est rendu plus façile par moyen de la procédure de śelection que préconiseBrown(1976). Vu l'analyse, on fait la distinction nette entre les facteurs et les réponses, et on concentre sur la localisation des interactions facteurs/réponses susceptibles d'être importantes. L'article est destiné à aller de pair à celui deWrigley(1980), qui met en oeuvre une analyse dite “logit” à partir des mêmes donné***. J. G. (1981) log-lineare Modelle, Ausfiltern und regionale Industriegutachten,Reg. Studies15,33–45. Diese Abhandlung benutzt hierarchische log-lineare Modelle zur Analyse einer Reihe entgegengesetzt klassifizierter kategorischer Daten, die von einem kürzlich in Nordirland durchgeführten regionalen Überblick der Industrie stammen. Die Daten stellen eine komplette 27Tafel dar. Die Auswahl eines passenden Modells wurde durch A
This paper reviews the analysis of prospective epidemiological studies using general linearmodels to describe disease Incidence, It is shown that, apart from problems arising from the large size of most studies of th...
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This paper reviews the analysis of prospective epidemiological studies using general linearmodels to describe disease Incidence, It is shown that, apart from problems arising from the large size of most studies of this type, these models may be fitted by maximum likelihood (using GLIM, for example) assuming a Poisson *** methods for dealing with large-scale data are discussed, and some simple procedures for dealing with common problems are *** relationship of the approach to multiple logistic analyses is indicated.
The paper uses two approaches to study whether aggregate fluctuations in employment and unemployment may be explained within a market clearing framework as intertemporal substitution in labour supply. First, log-linea...
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The paper uses two approaches to study whether aggregate fluctuations in employment and unemployment may be explained within a market clearing framework as intertemporal substitution in labour supply. First, log-linear equations for labour supply and unemployment are estimated using a forecasting model to measure wage and price expectations. Second, a utility function is used to derive and estimate an equation for labour supply as a function of the current real wage and consumption, The influence of expected future real wages and interest rates is captured by the consumption variable. The empirical results do not support the intertemporal substitution model. [ABSTRACT FROM AUTHOR]
作者：
GROSS, STAssociate Professor
Department of Statistics The City University of New York Baruch College New York NY 10010
Asymptotic power formulas for tests of independence against simple association models in I × J contingency tables with ordered categories are presented. Yates's score correlation test and Spearman's tied ...
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Asymptotic power formulas for tests of independence against simple association models in I × J contingency tables with ordered categories are presented. Yates's score correlation test and Spearman's tied rank correlation test are compared with a likelihood ratio test proposed by S. J. Haberman for testing independence in log-linear models with ordered classifications. Asymptotic power and relative efficiencies are derived under local alternatives that need not be included in the likelihood model assumed by Haberman's procedure. Some computations for real and fictitious data are presented.
This paper unites two different fields, survival and contingency table analysis, in a single analytical framework based on the log-linear model. We demonstrate that many currently popular approaches to modeling surviv...
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This paper unites two different fields, survival and contingency table analysis, in a single analytical framework based on the log-linear model. We demonstrate that many currently popular approaches to modeling survival data, including the approaches of Glasser (1967), Cox (1972), Breslow (1972, 1974), and Holford (1976), can be handled by using existing computer packages developed for the log-linear analysis of contingency table data. More important, we demonstrate that the log-linear modeling system used to characterize counted data structures directly characterizes survival data as well. Counted data methodologies for testing and estimation are also applicable here. Much of the theoretical basis for this work has been independently derived by Holford (1980) and Aitkin and Clayton (1980). The emphasis in this paper is not to develop new methodologies, but rather to present new uses and interpretations for already familiar methodologies. [ABSTRACT FROM AUTHOR]
作者：
Cohen, ArthurProfessor
Department of Statistics Rutgers University New Brunswick NJ 08903
Consider a three-way contingency table with factors A, B, and C. Assume factors A and B are independent for each given level of factor C. Inference procedures concerning the marginal means of the levels of factor A ar...
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Consider a three-way contingency table with factors A, B, and C. Assume factors A and B are independent for each given level of factor C. Inference procedures concerning the marginal means of the levels of factor A are studied. Maximum likelihood estimators, unbiased estimators, and uniformly minimum variance unbiased estimators are obtained. Exact variance formulas for the estimators are obtained. Large sample theory is developed and used for testing and confidence intervals. A variety of sampling models and generalizations are studied, including the case in which the number of levels of factor C is infinite. An example concerned with vaccine evaluation is given. [ABSTRACT FROM AUTHOR]
Errors in the collection of categorical data lead to misclassification of observed counts. Several authors have proposed a double sampling scheme. This article develops a method for analysis of double sampling data. F...
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Errors in the collection of categorical data lead to misclassification of observed counts. Several authors have proposed a double sampling scheme. This article develops a method for analysis of double sampling data. First, a log-linear model is selected for the misclassification matrix that relates the fallible to the correct data; then another log-linear model is built on the distribution of the correct classifications. Thus, the error structure can be utilized in inference of the relationships among the correct classifications. The statistical principles used are maximum likelihood estimation and goodness-of-fit tests. An example from epidemiology illustrates the methodology.
The likelihood ratio classification rule based on the location model is estimated given: (1) data consist of both binary and continuous variables; (2) some states have either zero frequency or too few observations, th...
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The likelihood ratio classification rule based on the location model is estimated given: (1) data consist of both binary and continuous variables; (2) some states have either zero frequency or too few observations, the case that usually happens in practice. An iterative proportional fitting of a convenient approximation of the log-linear models as well as a linear additive model are utilized in estimating the rule's parameters. Performance of the obtained rule is then assessed by estimated error rates.
Given the size (R .times. C) of an incomplete 2-way contingency table, the apriori cell probabilities, .***, (i = 1, 2, .cntdot..cntdot..cntdot., R;j = 1, 2, .cntdot..cntdot..cntdot., C), the program produces 5 arrays...
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Given the size (R .times. C) of an incomplete 2-way contingency table, the apriori cell probabilities, .***, (i = 1, 2, .cntdot..cntdot..cntdot., R;j = 1, 2, .cntdot..cntdot..cntdot., C), the program produces 5 arrays of smoothed cell counts after adjusting existing zeros to certain values according to .*** and a weighting factor, K, which is also computed together with the value of a risk function for each array. After selecting one of those arrays according to the value of the risk function, the program produces estimates for parameters of the saturated, independence and other hierarchical log-linear models in addition to the likelihood ratio for testing their degree of fit.
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