Registrations in epidemiological studies suffer from incompleteness, thus a general consensus is to use capture-recapture models. Lately, there has been a thrust to incorporate covariates which relate to the capture p...
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Registrations in epidemiological studies suffer from incompleteness, thus a general consensus is to use capture-recapture models. Lately, there has been a thrust to incorporate covariates which relate to the capture probabilities in order to improve the estimate of population size. Current approaches utilize covariates observed in all the pertinent registrations. In epidemiological applications, one often encounters capture-recapture data where some covariates are measured by some but not by all of the registrations under scrutiny. In this article, the usefulness of these types of covariates is evaluated and furthermore a methodology for analysing such capture-recapture data is presented. The methodology is illustrated by applying it to data on neural tube defects in the Netherlands. Copyright 2006 John Wiley & Sons, Ltd.
Kernel smoothing methods are used to extend the Poisson log-linear approach to the estimation of the size of population using multiple lists to an open population when the multiple lists are recorded at each time poin...
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Kernel smoothing methods are used to extend the Poisson log-linear approach to the estimation of the size of population using multiple lists to an open population when the multiple lists are recorded at each time point. The data is marginal as only the lists at each time point are available and the transitions of individuals between lists at different time points are not observable. Our analysis is motivated by and applied to data on the number of drug addicts in the Hong Kong Special Administrative Region.
The selling prices of used houses may not fully reflect the maintenance spending of current owners when prospective buyers are unable to conduct a thorough inspection before purchase. This article investigates how thi...
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The selling prices of used houses may not fully reflect the maintenance spending of current owners when prospective buyers are unable to conduct a thorough inspection before purchase. This article investigates how this resale externality problem affects the maintenance expenditures of homeowners. After considering both observable and unobservable repair expenses, the analysis shows that the resale externality reduces not only maintenance expenditures, but also household mobility. A treatment effects model is used to estimate the simultaneous relationship between mobility and maintenance in the Japanese resale housing market. The results indicate that the resale externality has a significant negative impact on maintenance expenditures.
This research examines empathic dispositions of 178 pre-service teachers. We analyzed open ended responses to animated narrative vignette simulations (ANVs), which served as stimulated experimental situations depictin...
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This research examines empathic dispositions of 178 pre-service teachers. We analyzed open ended responses to animated narrative vignette simulations (ANVs), which served as stimulated experimental situations depicting students in victim and perpetrator scenarios. Empathy was examined by addressing the following questions: (1) Do participants' responses differ over vignettes? (2) What is the dimensionality of the empathy construct? (3) Is word count an indicator of empathy? (4) Is there a dispositional effect? (5) To what extent do pre-service teachers express empathy? After the text responses of pre-service teachers were coded, log-linear and log-multiplicative association models, which have graphical representations, were used to analyze the data and to develop a context dependent measure of empathy. The results suggest that a single latent variable underlies the responses, and from our measurement model, very few teachers expressed empathy toward the victim in the ANVs. Published by Elsevier Inc.
This article bridges the permutation test of Moran's I to the residuals of a loglinear model under the asymptotic normality assumption. It provides the versions of Moran's I based on Pearson residuals (I-PR) a...
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This article bridges the permutation test of Moran's I to the residuals of a loglinear model under the asymptotic normality assumption. It provides the versions of Moran's I based on Pearson residuals (I-PR) and deviance residuals (I-DR) so that they can be used to test for spatial clustering while at the same time account for potential covariates and heterogeneous population sizes. Our simulations showed that both I-PR and I-DR are effective to account for heterogeneous population sizes. The tests based on I-PR and I-DR are applied to a set of log-rate models for early-stage and late-stage breast cancer with socioeconomic and access-to-care data in Kentucky. The results showed that socioeconomic and access-to-care variables can sufficiently explain spatial clustering of early-stage breast carcinomas, but these factors cannot explain that for the late stage. For this reason, we used local spatial association terms and located four late-stage breast cancer clusters that could not be explained. The results also confirmed our expectation that a high screening level would be associated with a high incidence rate of early-stage disease, which in turn would reduce late-stage incidence rates.
The log-linear model, with an alternative parameter coding scheme, is used in this paper to obtain estimates of international migration flows in situations where the data are inadequate or missing. The alternative par...
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The log-linear model, with an alternative parameter coding scheme, is used in this paper to obtain estimates of international migration flows in situations where the data are inadequate or missing. The alternative parameter coding scheme is particularly useful in constructing the origin-destination association stricture-a key element often required for more-accurate predictions. To illustrate the method, international migration flows between countries in the northern region of Europe during the 1999 - 2000 period are estimated.
Relative entropy identities yield basic decompositions of cat- egorical data log-likelihoods. These naturally lead to the development of information models in contrast to the hierarchical log-linear models. A recent s...
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Relative entropy identities yield basic decompositions of cat- egorical data log-likelihoods. These naturally lead to the development of information models in contrast to the hierarchical log-linear models. A recent study by the authors claried the principal dierence in the data likelihood analysis between the two model types. The proposed scheme of log-likelihood decomposition introduces a prototype of linear information models, with which a basic scheme of model selection can be formulated accordingly. Empirical studies with high-way contingency tables are exem- plied to illustrate the natural selections of information models in contrast to hierarchical log-linear models.
This paper investigates the combined effect of driver nationality and several road characteristics (area type, at or not at junction, lighting conditions) on accident fault risk. Data from the national accident databa...
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This paper investigates the combined effect of driver nationality and several road characteristics (area type, at or not at junction, lighting conditions) on accident fault risk. Data from the national accident database of Greece are used to calculate accident relative fault risk rates under induced exposure assumptions. A log-linear analysis is then used to examine first- and higher-order effects within three or more variable groups. The examination of the second-order interaction among the accident fault risks of various driver nationalities at or not at junction was found to be significant. On the contrary, the respective combined effects of area type and lighting conditions were found to be non-significant. It was also shown that roadway features do not affect accident fault risk in a combined way. Results clearly indicate that foreign drivers in Greece are at increased risk. Moreover, foreign nationalities corresponding to permanent residents (i.e. Greeks and Albanians) appear to be at lower fault risk compared to foreign nationalities corresponding to tourists and visitors (e.g. EU Nationals). The effects of the various road characteristics do not modify these general trends.
This paper concerns the search for optimal or nearly optimal batting orders in one-day cricket. A search is conducted over the space of permutations of batting orders where simulated annealing is used to explore the s...
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This paper concerns the search for optimal or nearly optimal batting orders in one-day cricket. A search is conducted over the space of permutations of batting orders where simulated annealing is used to explore the space. A non-standard aspect of the optimization is that the objective function (which is the mean number of runs per innings) is unavailable and is approximated via simulation. The simulation component generates runs ball by ball during an innings taking into account the state of the match and estimated characteristics of individual batsmen. The methods developed in the paper are applied to the national team of India based on their performance in one-day international cricket matches. (c) 2004 Elsevier Ltd. All rights reserved.
Researchers interested in the association of a predictor with an outcome will often collect information about that predictor from more than one source. Standard multiple regression methods allow estimation of the effe...
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Researchers interested in the association of a predictor with an outcome will often collect information about that predictor from more than one source. Standard multiple regression methods allow estimation of the effect of each predictor on the outcome while controlling for the remaining predictors. The resulting regression coefficient for each predictor has an interpretation that is conditional on all other predictors. In settings in which interest is in comparison of the marginal pairwise relationships between each predictor and the outcome separately (e.g., studies in psychiatry with multiple informants or comparison of the predictive values of diagnostic tests), standard regression methods are not appropriate. Instead, the generalized estimating equations (GEE) approach can be used to simultaneously estimate, and make comparisons among, the separate pairwise marginal associations. In this paper, we consider maximum likelihood (ML) estimation of these marginal relationships when the outcome is binary. ML enjoys benefits over GEE methods in that it is asymptotically efficient, can accommodate missing data that are ignorable, and allows likelihood-based inferences about the pairwise marginal relationships. We also explore the asymptotic relative efficiency of ML and GEE methods in this setting.
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