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Random effects model

About: Random effects model is a research topic. Over the lifetime, 8388 publications have been published within this topic receiving 438823 citations. The topic is also known as: random effects & random effect.


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Journal ArticleDOI
TL;DR: In this paper, a two-stage technique for estimation and inference in probit models with structural group effects is proposed. But this technique is not suitable for estimating the conditional mean of a latent variable.

92 citations

Journal ArticleDOI
TL;DR: In this paper, the effects of information on residential demand for electricity, using data from a Japanese experiment, were measured using a continuous display, electricity use monitoring device installed at their residence.
Abstract: This paper measures the effects of information on residential demand for electricity, using data from a Japanese experiment. In the experiment, households had a continuous-display, electricity use monitoring device installed at their residence. The monitor was designed so that each consumer could easily look at graphs and tables associated with the consumer's own usage of electricity at any time during the experiment. The panel data were used to estimate a random effects model of electricity and count data models of monitor usage. The results indicate that monitor usage contributed to energy conservation.

92 citations

Journal ArticleDOI
TL;DR: For data sets with complex GE, modeling GE using the FA model improved the predictability of the model up to 6%.
Abstract: Fixed linear models have been used for describing genotype x environment interaction (GE). Previous attempts have been made to assess the predictive ability of some linear mixed models when GE components are treated as random effects and modeled by the factor analytic (FA) model. This study compares the predictive ability of linear mixed models when the GE is modeled by the FA model with that of simple linear mixed models when the GE is not modeled. A cross-validation scheme is used that randomly deletes some genotypes from sites; the values for these genotypes are then predicted by the different models and correlated with their observed values to assess model accuracy. A total of six multienvironment trials (one potato [Solanum tuberosum L.] trial, three maize [Zea mays L.] trials, and two wheat [Triticum aestivum L.] trials) with GE of varying complexity were used in the evaluation. Results show that for data sets with complex GE, modeling GE using the FA model improved the predictability of the model up to 6%. When GE is not complex, most models (with and without FA) gave high predictability, and models with FA did not seem to lose much predictive ability. Therefore, we concluded that modeling GE with the FA model is a good thing.

92 citations

Journal ArticleDOI
TL;DR: In this paper, a hierarchical discrete time survival model for the analysis of the 2000 Malawi Demographic and Health Survey data to assess the determinants of transition to marriage among women in Malawi is presented.
Abstract: Summary. The paper presents a hierarchical discrete time survival model for the analysis of the 2000 Malawi Demographic and Health Survey data to assess the determinants of transition to marriage among women in Malawi. The model explicitly accounts for the unobserved heterogeneity by using family and community random effects with cross-level correlation structure. A nonparametric technique is used to model the base-line discrete hazard dynamically. Parameters of the model are computed by using a Markov chain Monte Carlo algorithm. The results show that rising age at marriage is a combination of birth cohort and education effects, depends considerably on the family and to some extent on the community in which a woman resides and the correlation between family and community random effects is negative. These results confirm a downward trend in teenage marriage and that raising women's education levels in subSaharan Africa has the beneficial effect of increasing age at marriage, and by implication reducing total fertility rates. The negative correlation between family and community random effects has policy implications in that targeting communities with an intervention to increase age at first marriage may not necessarily yield reduced fertility levels in individual families. A campaign that is geared towards individual families would achieve the desired goals. Overall, the findings point to the need for the Government in Malawi to enact public policies which are geared at vastly improving women's education at higher levels. The variation in marriage rates over families poses problems in delivering the policy, since particular policies must be devised for specific groups of families to accomplish the required social and health objectives.

92 citations

Journal ArticleDOI
TL;DR: It is shown that bias can be induced for regression coefficients when random effects are truly correlated but misspecified as independent in a 2-part mixed model.
Abstract: Semicontinuous data in the form of a mixture of zeros and continuously distributed positive values frequently arise in biomedical research. Two-part mixed models with correlated random effects are an attractive approach to characterize the complex structure of longitudinal semicontinuous data. In practice, however, an independence assumption about random effects in these models may often be made for convenience and computational feasibility. In this article, we show that bias can be induced for regression coefficients when random effects are truly correlated but misspecified as independent in a 2-part mixed model. Paralleling work on bias under nonignorable missingness within a shared parameter model, we derive and investigate the asymptotic bias in selected settings for misspecified 2-part mixed models. The performance of these models in practice is further evaluated using Monte Carlo simulations. Additionally, the potential bias is investigated when artificial zeros, due to left censoring from some detection or measuring limit, are incorporated. To illustrate, we fit different 2-part mixed models to the data from the University of Toronto Psoriatic Arthritis Clinic, the aim being to examine whether there are differential effects of disease activity and damage on physical functioning as measured by the health assessment questionnaire scores over the course of psoriatic arthritis. Some practical issues on variance component estimation revealed through this data analysis are considered.

91 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
2023198
2022433
2021409
2020380
2019404