000 | 07488nam a2200301Ia 4500 | ||
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001 | ocm61880159 | ||
003 | OCoLC | ||
008 | 051008s2005 txua 001 0 eng d | ||
020 | _a1597180084 | ||
040 |
_aNDB _cNDB |
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082 | 0 | _a519.50243 RAB | |
100 | 1 | _aRabe-Hesketh, S. | |
245 | 1 | 0 |
_aMultilevel and longitudinal modeling using Stata / _cSophia Rabe-Hesketh, Anders Skrondal. |
260 |
_aCollege Station, Tex. : _bStata Press, _cc2005. |
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300 |
_axxiii, 317 p. : _bill. ; _c24 cm. |
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505 | 0 | _a 1. LINEAR VARIANCE-COMPONENTS MODELS:- Introduction--How reliable are expiratory flow measurements?--The variance- components model--Model specification and path diagram--Error components, variance components, and relaibility--Intraclass correlation--Modeling the mini wright measurements--Estimation using xtreg--Estimation using xtmixed--Estimation using gllamm--Relative and absolute agreement--Estimation methods--Assigning values to the random intercepts--Maximum likelihood estimation--Implementation via OLS regression--Implementation via the mean total residual--Empirical Bayes prediction--Empirical Bayes variances--Summary and further reading--Exercises--2. LINEAR RANDOM-INTERCEPT MODELS:- Introduction--Are tax preparers useful?--The longitudinal data structure--Panel data and correlated residuals--The random-intercept model--Estimation using xtreg--Estimation using xtmixed--Different kinds of effects in panel models--Between -taxpayer effects--within-taxpayer effect--Relations among the estimators--Endogeneity and between-taxpayer effects--Residual diagnostics-- Summary and further reading--Exercises--3. LINEAR RANDOM-COEFFICIENT AND GROWTH-CURVE MODELS:- Introduction--How effective are different schools?--Separate linear regressions for each school--The random-coefficient model--Specification and interpretation of a random-coefficient model--Estimation and prediction using xtmixed--Estimation of random-intercept model--Estimation of random-coefficient model--Empirical Bayes prediction using xtmixed--Estimation and prediction using gllamm--Estimation of random-intercept model--Estimation of random-coefficient model--Empirical Bayes prediction--How do children grow?--Growth-curve modeling--Observed growth trajectories--Estimation using xtmixed --Quadratic growth model with random intercept--Quadratic growth model with random intercept and random slope--Including a child-level covariate--Estimation using gllamm--Quadratic growth model with random intercept--Quadratic growth model with random intercept and random slope--Including a child-level covariate--Two-stage model formulation--Model specification--Estimation--Prediction of trajectories for individual children--Complex level-1 variation or heteroskedasticity-Summary and further reading--Exercises--4. DICHOTOMOUS OR BINARY RESPONSES:- Models for dichotomous responses--Generalized linear model formulation--Latent-response formulation--Logistic regression--Probit regression--Which treatment is best for toenail infection?--The longitudinal data structure--Population-averaged or marginal probabilities--Random-intercept logistic regression--Subject-specific vs. population-averaged relationships--maximum likelihood estimation using adaptive quadrature--Some practical considerations--Empirical Bayes (EB) predictions--EB prediction of random effects--EB prediction of response probabilities--Other approaches to clustered dichotomous data--Conditional logistic regression--Generalised estimating equations (GEE)-- Summary and further reading--Exercises--5. ORDINAL RESPONSES:- Introduction--Cumulative models for ordinal responses--Generalised linear model formulation--Latent-response formulation--Proportional odds--Identification--Are antipsychotic drugs effective for patients with schizophrenia?--Longitudinal data structure and graphs--The longitudinal data structure--Plotting cumulative proportions--Plotting cumulative logits and transforming the time scale--A proportional-odds model--Model specification--Estimation--A random-intercept proportional-odds model--Model specification--Estimation--A random co-efficient proportional-odds model--Model specification--Estimation--Marginal and patient-specific probabilities--Marginal probabilities--Patient-specific cumulative response probabilities--Do experts differ in their grading of student essays?--A random-intercept model with grader bias--Model specification--Estimation--Including grader-specific measurement error variances--Model specification--Estimation--Including grader-specific thresholds--Model specification--Estimation--Summary and further reading--Exercises--6. COUNTS:- Introduction--Types of counts--Poisson models for counts--Did the German health-care reform reduce the number of doctor visits?--Longitudinal data structure--Poisson regression ignoring overdispersion and clustering--Model specification--Estimation--Poisson regression with overdispersion but ignoring clustering--Using a level-1 random intercept--Model specification--Estimation--Quasilikelihood--Specification--Estimation--Random-intercept poisson regression--Model specification--Estimation--Random-coefficient poisson regression--Model specification--Estimation--Other approaches to clustered counts--Conditional Poisson regression--Generalized estimating equations (GEE)--Which Scottish counties have a high risk of lip cancer?--Standardized mortality ratios--Random-intercept Poisson regression--Model specification--Estimation--Introducing a county-level covariate--Prediction--Nonparametric maximum likelihood estimation--Specification--Estimation--Prediction--Summary and further reading--Exercises--7. HIGHER LEVEL MODELS AND NESTED RANDOM EFFECTS:- Introduction--Which method is best for measuring expiratory flow?--Two-level variance-components models--Model specification--Estimation--Three level variance-components models--Model specification--Different types of intraclass correlation--Three-stage formulation--Estimation using xtmixed--Prediction using xtmixed--Did the Guatemalan immunization campaign work?--A three-level logistic random-intercept model--Model specification--Different types of intraclass correlations for the latent responses--Three stage formulation--Estimation--Introducing a random coefficient at levle 3--Prediction--Summary and further reading--Exercises--8. CROSSED RANDOM EFFECTS:- Introduction--How does investment depend on expected profit and capital stock?--A two-way error-components model--Model specification--Intraclass correlations--Estimation--Prediction-- How much do primary and secondary schools affect attainment at age 16?-- An addictive crossed random-effects model--Specification--Estimation--Including a random interaction--Model specifications--Interclass correlations--Estimation--Some diagnostics--A trick requiring fewer random effects--Summary and further reading--Exercises. | |
630 | 0 | 0 | _aStata. |
650 | 0 |
_aSocial sciences _xStatistical methods _xComputer programs. |
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650 | 0 |
_aStatistics _xComputer programs. |
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650 | 0 | _aLongitudinal method. | |
700 | 1 | _aSkrondal, Anders. | |
902 | _a170814 | ||
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_eclaim1 was sent 07-07-2006 _eclaim2 was sent 28-08-2006 _eclaim3 was sent 19-10-2006 _fMary McDonnell _lnlib _mdon |
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