MATH 6643 Summer 2012 Applications of Mixed Models/Students/smithce/Model4

(Difference between revisions)
 Revision as of 10:44, 29 May 2012 (view source)Smithce (Talk | contribs) (Created page with " Combined Model :[itex]mathach_{ij} = \underbrace{{\color{Red}\gamma_{00}} + {\color{Red}\gamma_{01}Sector_j} + {\color{Red}\gamma_{02}ses.m_j} + {\color{Blue}\gamma_{10}...")← Older edit Revision as of 10:48, 29 May 2012 (view source)Smithce (Talk | contribs) Newer edit → Line 87: Line 87: "Compositional" =  c( 0,1,0,1,0))) "Compositional" =  c( 0,1,0,1,0))) wald( fitca,L ) wald( fitca,L ) + + + {| {{table}} + | ||numDF||denDF||F.value||p.value + |- + | Effect of ses||2||77||40.83481||<.00001 + |} + + + {| {{table}} + | ||Estimate||Std.Error||DF||t-value||p-value||Lower 0.95||Upper 0.95 + |- + | Within-school||1.528862||0.245895||3602||6.217541||<.00001||1.046755||2.010969 + |- + | Contextual||3.033531||0.594078||77||5.106285||<.00001||1.850571||4.216492 + |- + | Compositional||4.562394||0.593325||77||7.68954||<.00001||3.380933||5.743854 + |}

Revision as of 10:48, 29 May 2012

Combined Model

$mathach_{ij} = \underbrace{{\color{Red}\gamma_{00}} + {\color{Red}\gamma_{01}Sector_j} + {\color{Red}\gamma_{02}ses.m_j} + {\color{Blue}\gamma_{10}}ses_{ij} + {\color{Blue}\gamma_{11}Sector_j}ses_{ij}}_{Fixed} + \underbrace{{\color{Red}u_{0j}} + {\color{Blue}u_{1j}}ses.d_{ij} + r_{ij}}_{Random}$

Fixed Portion of the Model Equivalent to FE model for Model 2 (LINK).

${\color{Red}\gamma_{00}} + {\color{Red}\gamma_{01}}Sector_j + {\color{Red}\gamma_{02}}ses.m_j + {\color{Blue}\gamma_{10}}ses_{ij} + {\color{Blue}\gamma_{11}}Sector_jses_{ij}$

Random Portion of the Model Non-equivalent RE model as compared to Model 2 (LINK).

${\color{Red}u_{0j}} + {\color{Blue}u_{1j}}ses.d_{ij} + r_{ij}$
${\color{Red}u_{0j}} + {\color{Blue}u_{1j}}(ses_{ij} - ses.m_{j}) + r_{ij}$

fitca <- lme( mathach ~ ses * Sector + ses.m, dd, random = ~ 1 + ses.d | id )  #c# Model 4 #c#


Linear mixed-effects model fit by REML
Data: dd

 AIC BIC logLik 23889.77 23945.66 -11935.88

Random effects:
Formula: ~1 + ses.d | id
Structure: General positive-definite, Log-Cholesky parametrization

 StdDev Corr (Intercept) 1.7465424 (Intr) ses.d 0.6444623 0.398 Residual 6.0649774

Fixed effects: mathach ~ ses * Sector + ses.m

 Value Std.Error DF t-value p-value (Intercept) 13.841459 0.3267406 3602 42.36223 0.00E+00 ses 1.528862 0.245895 3602 6.21754 0.00E+00 SectorPublic -1.830417 0.4579895 77 -3.99664 1.00E-04 ses.m 3.033531 0.5940779 77 5.10629 0.00E+00 ses:SectorPublic 1.354043 0.3243585 3602 4.17453 0.00E+00

Correlation:

 (Intr) ses SctrPb ses.m ses 0.121 SectorPublic -0.734 -0.114 ses.m -0.157 -0.21 0.244 ses:SectorPublic -0.068 -0.728 0.155 0.014

Standardized Within-Group Residuals:

 Min Q1 Med Q3 Max -3.10386562 -0.73369552 0.02217222 0.75083942 2.85079637

Number of Observations: 3684
Number of Groups: 80

L <- list( 'Effect of ses' = rbind(
"Within-school" =  c( 0,1,0,0,0),
"Contextual"    =  c( 0,0,0,1,0),
"Compositional" =  c( 0,1,0,1,0)))
wald( fitca,L )


 numDF denDF F.value p.value Effect of ses 2 77 40.83481 <.00001

 Estimate Std.Error DF t-value p-value Lower 0.95 Upper 0.95 Within-school 1.528862 0.245895 3602 6.217541 <.00001 1.046755 2.010969 Contextual 3.033531 0.594078 77 5.106285 <.00001 1.850571 4.216492 Compositional 4.562394 0.593325 77 7.68954 <.00001 3.380933 5.743854