[讨论]Stata: Resources For Learning Stata

Getting Started with STATA for MS Windows: A Brief Introduction - By Robert A. Yaffee. This Introduction to STATA for Windows is a large (2.1 MB) PDF file that may take a minute to load into your Acrobat Reader. Please be patient and wait for it to load.

Elementary Epidemiological Data Analysis with STATA (339K PDF) - By Robert A. Yaffee.

Basic Epidemilogical Analysis with Stata (167K PDF) - class notes by Robert A. Yaffee.

Regression Analysis (OLS and Robust) with STATA - Lecture Notes (234K PDF) - By Robert A. Yaffee. Intermediate Stata Lecture Notes.

Event History Analysis using Stata - Lecture notes in powerpoint - By Robert A. Yaffee.

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[下载]gllamm for complex problems

General notion

gllamm stands for Generalized Linear Latent And Mixed Models. The primary aims of this software is to provide a maximum likelihood framework for models with unobserved components, such as multilevel models, certain latent variable models, panel data models, or models with common factors.

The official website of the software is http://www.gllamm.org maintained by one of the authors, Sophia Rabe-Hesketh. She and other authors of gllamm, Anders Skrondal and Andrew Pickles, published a book "Generalized Latent Variable Modelling".

gllamm is implemented as a system of Stata modules. To install it on your Stata, type

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Abstract

This manual describes a Stata program gllamm that can estimate Generalized Linear Latent and Mixed Models (GLLAMMs). GLLAMMs are a class of multilevel latent variable models for (multivariate) responses of mixed type including continuous responses, counts, duration/survival data, dichotomous, ordered and unordered categorical responses and rankings. The latent variables (common factors or random effects) can be assumed to be discrete or to have a multivariate normal distribution. Examples of models in this class are multilevel generalized linear models or generalized linear mixed models, multilevel factor or latent trait models, item response models, latent class models and multilevel structural equation models. The program can be downloaded from http://www.gllamm.org.

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[讨论]Stata: Resources For Learning Stata
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Papers using gllamm

2006

Aitkin, I. and Scott, J. (2006). The effect of missing data on covariates in survival analysis. Submitted for publication.

Andreß, H. J. (2006). Zur Entwicklung von Lebensstandard und Deprivation in Deutschland von 1996 bis 2003. Vierteljahrshefte zur Wirtschaftsforschung, 75 (1).

Bertelli, A. M. nm(2006). Motivation Crowding and the Federal Civil Servant: Evidence from the U.S. Treasury. International Public Management Journal 9 (1), 1-21.

Bottai, M., Salvati, N. and Orsini, N. (2006). Multilevel models for analyzing people抯 daily movement behavior, Journal of Geographical Systems.

Bramon, E., Dempster, E., Frangou, S., McDonald, C., Schoenberg, P., MacCabe, J. H., Walshe, M., Sham, P., Collier, D. and Murray, R. M. (2006). Is there an association between the COMT gene and P300 endophenotypes? European Psychiatry 21 (1), 70-73.

Fieldhouse, E., Pickles, A., Shyrance, N., Johnson, J. and Kingsley, P. (2006). Modeling multiparty elections, preference classes and strategic voting. Working paper, The University of Manchester, UK.

Grilli, L. and Rampichini, C. (2006). A review of random effects modelling using gllamm in Stata. In Software Reviews of Multilevel Analysis Packages. Centre for Multilevel Modelling. University of Bristol, UK.

Jæger, M. M. (2006). Welfare regimes and attitudes towards redistribution: The regime hypothesis revisited. European Sociological Review 22 (2).

Jæger, M. M. (2006). What makes people support public responsibility for welfare provision: Self-interest or political ideology? Acta Sociologica 49 (3).

Klassen, A. C., Culticlo, F., Kulldorff, N., Alberg, A. J., Platz, E. A. and Neloms, S. T. (2006). Missing stage and grade in Maryland prostate cancer surveillance data, 1992-1997. American Journal of Preventive Medicine 30 (2), S77-S87.

Knotts, H. G. and Haspel, M. (2006). The impact of gentrification on voter turnout. Social Science Quarterly 87 (1), 110-121.

Marsden, P. V., Landon, B. E., Wilson, I. B., McInnes, K., Hirschhorn, L. R., Ding, L., and Cleary, P. D. (2006). The reliability of survey assessments of characteristics of medical clinics. Health Services Research 41 (1), 265-283.

Miranda, A. and Rabe-Hesketh, S. (2006). Maximum likelihood estimation of endogenous switching and sample selection models for binary, count, and ordinal variables. Submitted for publication.

Prentice, J. C. (2006). Neighborhood effects on primary care access in Los Angeles. Social Science & Medicine 63, 1291-1303.

Rabe-Hesketh, S. and Skrondal, A. (2006). Multilevel modeling of complex survey data. Journal of the Royal Statistical Society, Series A. In press.

Rabe-Hesketh, S. and Skrondal, A. (2006). Multilevel and latent variable modelling with composite links and exploded likelihoods. Submitted for publication.

Rabe-Hesketh, S., Skrondal, A. and Zheng, X. (2006). Multilevel structural equation modeling. In S.-Y. Lee (Ed.). Handbook on Structural Structural Equation Models. Amsterdam: Elsevier. Forthcoming.

Skrondal, A. and Rabe-Hesketh, S. (2006). Models for longitudinal data. In de Leeuw, J. (Ed.) Handbook for Multilevel Analysis. New York: Springer. Forthcoming.

Solis-Trapala, J. L. and Farewell, V. T. (2006). A note on robust inference from a conditional Poisson model. Biometrical Journal 48, 117-130.

Torsheim, T., Currie, C., Boyce, W., and Samdal, O. (2006). Country material distribution and adolescents' perceived health: multilevel study of adolescents in 27 countries. Journal of Epidemiology and Community Health 60 (2), 156-161.

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[此贴子已经被作者于2006-5-6 3:33:49编辑过]

STATA里的固定效应模型究竟是个体固....应，还是个体固定都算？[长]

用stata如何检验panel的自相关和异方差