Introductory And Intermediate Growth Models - Mplus

More documents

Recommendations

Info

Output Excerpts Schizophrenia Data Growth ModelFor Binary Outcomes With A Treatment VariableTests Of Model Fitn = 313LoglikelihoodHO Value -486.337Information CriteriaNumber of Free Parameters 7Akaike (AIC) 986.674Bayesian (BIC) 1012.898Sample-Size Adjusted BIC 990.696(n* = (n + 2) / 24)207Output Excerpts Schizophrenia Data Growth ModelFor Binary Outcomes With A TreatmentVariable (Continued)Selected EstimatesI ONDRUGS ONDRUGI WITHSInterceptsISThresholdsILLNESS1$1ILLNESS2$1ILLNESS4$1ILLNESS5$1Residual VariancesISEstimates S.E. Est./S.E. Std StdYX-0.429 0.825 -0.521 -0.156 -0.063-0.651 0.259 -2.512 -0.684 -0.276-0.925 0.621 -1.489 -0.353 -0.3530.000 0.000 0.000 0.000 0.000-0.555 0.255 -2.182 -0.583 -0.583-5.706 1.047 -5.451-5.706 1.047 -5.451-5.706 1.047 -5.451-5.706 1.047 -5.4517.543 3.213 2.348 0.996 0.9960.838 0.343 2.440 0.924 0.924208104
Further Readings On Growth AnalysisWith Categorical OutcomesFitzmaurice, G.M., Laird, N.M. & Ware, J.H. (2004). Appliedlongitudinal analysis. New York: Wiley.Gibbons, R.D. & Hedeker, D. (1997). Random effects probit andlogistic regression models for three-level data. Biometrics, 53,1527-1537.Hedeker, D. & Gibbons, R.D. (1994). A random-effects ordinalregression model for multilevel analysis. Biometrics, 50, 933-944.Muthén, B. (1996). Growth modeling with binary responses. In A. V.Eye, & C. Clogg (Eds.), Categorical variables in developmentalresearch: methods of analysis (pp. 37-54). San Diego, CA:Academic Press. (#64)Muthén, B. & Asparouhov, T. (2002). Latent variable analysis withcategorical outcomes: Multiple-group and growth modeling inMplus. Mplus Web Note #4 (www.statmodel.com).209References(To request a Muthén paper, please email bmuthen@ucla.edu.)Analysis With Longitudinal DataIntroductoryBollen, K.A. & Curran, P.J. (2006). Latent curve models. A structuralequation perspective. New York: Wiley.Collins, L.M. & Sayer, A. (Eds.) (2001). New methods for the analysis ofchange. Washington, D.C.: American Psychological Association.Curran, P.J. & Bollen, K.A. (2001). The best of both worlds: Combiningautoregressive and latent curve models. In Collins, L.M. & Sayer, A.G.(Eds.) New methods for the analysis of change (pp. 105-136). Washington,DC: American Psychological Association.Duncan, T., Duncan S. & Strycker, L. (2006). An introduction to latentvariable growth curve modeling. Second edition. Lawrence Erlbaum: NewYork.Goldstein, H. (2003). Multilevel statistical models. Third edition. London:Edward Arnold.210105
Page 1 and 2:
Mplus Short CoursesTopic 3Growth Mo
Page 3 and 4:
Statistical Analysis With Latent Va
Page 5 and 6:
General Latent Variable Modeling Fr
Page 7 and 8:
Overview Of Mplus Courses (Continue
Page 9 and 10:
Mean CurveMath Achievement40 50 60
Page 11 and 12:
Loneliness In TwinsAge range: 13-85
Page 13 and 14:
Individual Development Over Time(1)
Page 15 and 16:
Comparison Summary Of Multilevel,Mi
Page 17 and 18:
Random Effects: SEM AndMultilevel M
Page 19 and 20:
Multilevel Modeling In ALatent Vari
Page 21 and 22:
Individual Development Over Timeyi
Page 23 and 24:
Interpretation Of The Linear Growth
Page 25 and 26:
Latent Growth Model ParametersFor F
Page 27 and 28:
Growth Model Covariancesy ti= η 0i
Page 29 and 30:
CFA Modeling Estimation And Testing
Page 31 and 32:
Alternative Growth Model Parameteri
Page 33 and 34:
LSAY Math AchievementMean CurveMath
Page 35 and 36:
TITLE:DATA:VARIABLE:MODEL:Input For
Page 37 and 38:
Output Excerpts LSAY Linear GrowthM
Page 39 and 40:
Output Excerpts LSAY Linear Growth
Page 41 and 42:
Output Excerpts LSAY:Adding Correla
Page 43 and 44:
Time-Invariant AndTime-Varying Cova
Page 45 and 46:
Output Excerpts LSAY Growth ModelWi
Page 47 and 48:
Output Excerpts LSAY Growth ModelWi
Page 50 and 51:
Centering• Centering determines t
Page 52 and 53:
Further Readings On Introductory Gr
Page 54 and 55: Growth Model With Free Time Scores1
Page 56 and 57: Input Excerpts For LSAYLinear Growt
Page 58 and 59: Quadratic growth modelSpecifying Ti
Page 60 and 61: Piecewise Growth Modeling• Can be
Page 62 and 63: Output Excerpts LSAY Piecewise Grow
Page 64 and 65: Growth Modeling In Multilevel Terms
Page 66 and 67: Output Excerpts For Growth Model Wi
Page 68 and 69: Maximum-Likelihood AlternativesNote
Page 70 and 71: Output Excerpts Model M1TESTS OF MO
Page 72 and 73: 72143Output Excerpts Model M1 (Cont
Page 74 and 75: Output Excerpts Model M1 (Continued
Page 76 and 77: Input Excerpt Model M3ANALYSIS:TYPE
Page 78 and 79: Time-Varying CovariatesRepresenting
Page 80 and 81: Regressions Among Random Effects159
Page 82 and 83: Output Excerpts Growth Model With A
Page 84 and 85: Interpreting The Effect Of The Inte
Page 86 and 87: Multiple Processes• Parallel proc
Page 88 and 89: math7 math8 math9math10imsmmothedia
Page 90 and 91: Output Excerpts LSAY ParallelProces
Page 92 and 93: Categorical Outcomes: Logit And Pro
Page 94 and 95: Logistic Regression And Log Odds (C
Page 96 and 97: Growth Models With Categorical Outc
Page 98 and 99: Input For Schizophrenia Data Growth
Page 100 and 101: Output Excerpts Schizophrenia Data
Page 102 and 103: Output Excerpts Schizophrenia Data
Page 106 and 107: References (Continued)Jennrich, R.I
Page 108 and 109: References (Continued)Ferrer, E. &
show all

Introductory And Intermediate Growth Models - Mplus

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?