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Created June 27, 2012 19:34
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poly(,3) raw=T vs raw=F
Raw
gistfile1.txt
> raw_c3_a3
Linear mixed model fit by REML ['lmerMod']
Formula: churchattendance ~ poly(cohort_c, 3, raw = T) * poly(age_c, 3, raw = T) + ctd_c + dropoutalive + obs_c + (1 + poly(age_c, 3, raw = T) | PERSNR)
Data: long.kg
REML criterion at convergence: 316048.9
Random effects:
Groups Name Variance Std.Dev. Corr
PERSNR (Intercept) 0.6409284 0.80058
poly(age_c, 3, raw = T)1 0.1641992 0.40522 0.131
poly(age_c, 3, raw = T)2 0.0129075 0.11361 -0.710 0.174
poly(age_c, 3, raw = T)3 0.0006747 0.02598 -0.036 -0.970 -0.381
Residual 0.2816139 0.53067
Number of obs: 152065, groups: PERSNR, 28984
Fixed effects:
Estimate Std. Error t value
(Intercept) 8.292e-01 1.062e-02 78.10
poly(cohort_c, 3, raw = T)1 -1.710e-01 1.447e-02 -11.82
poly(cohort_c, 3, raw = T)2 3.590e-02 9.708e-03 3.70
poly(cohort_c, 3, raw = T)3 -1.056e-02 1.158e-02 -0.91
poly(age_c, 3, raw = T)1 -9.993e-02 1.322e-02 -7.56
poly(age_c, 3, raw = T)2 -3.480e-02 8.901e-03 -3.91
poly(age_c, 3, raw = T)3 -3.966e-02 1.159e-02 -3.42
ctd_c -4.572e-02 5.075e-03 -9.01
dropoutalive 1.261e-02 1.066e-02 1.18
obs_c 1.417e-02 1.417e-03 10.00
poly(cohort_c, 3, raw = T)1:poly(age_c, 3, raw = T)1 -1.186e-02 1.692e-02 -0.70
poly(cohort_c, 3, raw = T)2:poly(age_c, 3, raw = T)1 -5.610e-02 3.441e-02 -1.63
poly(cohort_c, 3, raw = T)3:poly(age_c, 3, raw = T)1 -2.446e-03 2.166e-03 -1.13
poly(cohort_c, 3, raw = T)1:poly(age_c, 3, raw = T)2 -1.137e-01 3.439e-02 -3.31
poly(cohort_c, 3, raw = T)2:poly(age_c, 3, raw = T)2 -2.131e-02 4.327e-03 -4.92
poly(cohort_c, 3, raw = T)3:poly(age_c, 3, raw = T)2 -1.925e-03 4.392e-04 -4.38
poly(cohort_c, 3, raw = T)1:poly(age_c, 3, raw = T)3 -1.650e-02 2.297e-03 -7.19
poly(cohort_c, 3, raw = T)2:poly(age_c, 3, raw = T)3 -5.212e-03 4.552e-04 -11.45
poly(cohort_c, 3, raw = T)3:poly(age_c, 3, raw = T)3 -4.447e-04 5.968e-05 -7.45
Correlation of Fixed Effects:
(Intr) ply(c_,3,r=T)1 ply(c_,3,r=T)2 ply(c_,3,r=T)3 ply(g_,3,r=T)1 ply(g_,3,r=T)2 ply(g_,3,r=T)3
ply(c_,3,r=T)1 -0.173
ply(c_,3,r=T)2 -0.424 -0.186
ply(c_,3,r=T)3 -0.031 -0.550 0.340
ply(g_,3,r=T)1 -0.073 0.778 -0.264 -0.575
ply(g_,3,r=T)2 -0.269 -0.105 0.734 0.318 -0.164
ply(g_,3,r=T)3 -0.045 -0.490 0.375 0.941 -0.565 0.399
ctd_c -0.003 0.007 0.010 0.019 0.000 0.005 0.031
dropoutaliv -0.445 0.116 0.019 0.020 0.145 0.018 0.008
obs_c 0.180 -0.545 0.098 0.050 -0.585 0.078 0.045
p(_,3,r=T)1:(_,3,r=T)1 -0.173 -0.179 0.848 0.365 -0.211 0.906 0.423
p(_,3,r=T)2:(_,3,r=T)1 -0.047 -0.463 0.351 0.982 -0.547 0.370 0.971
p(_,3,r=T)3:(_,3,r=T)1 -0.271 0.035 0.648 -0.014 -0.030 0.502 0.089
p(_,3,r=T)1:(_,3,r=T)2 -0.035 -0.474 0.355 0.961 -0.523 0.396 0.989
p(_,3,r=T)2:(_,3,r=T)2 -0.133 0.046 0.515 -0.034 0.036 0.583 0.089
p(_,3,r=T)3:(_,3,r=T)2 -0.006 0.370 -0.134 -0.068 0.155 0.211 0.000
p(_,3,r=T)1:(_,3,r=T)3 -0.178 0.103 0.438 -0.051 0.044 0.645 0.084
p(_,3,r=T)2:(_,3,r=T)3 0.071 0.233 -0.180 -0.087 0.293 0.216 -0.015
p(_,3,r=T)3:(_,3,r=T)3 0.268 -0.151 -0.132 -0.023 0.192 -0.003 -0.016
ctd_c drptlv obs_c p(_,3,r=T)1:(_,3,r=T)1 p(_,3,r=T)2:(_,3,r=T)1 p(_,3,r=T)3:(_,3,r=T)1
ply(c_,3,r=T)1
ply(c_,3,r=T)2
ply(c_,3,r=T)3
ply(g_,3,r=T)1
ply(g_,3,r=T)2
ply(g_,3,r=T)3
ctd_c
dropoutaliv 0.053
obs_c -0.049 -0.155
p(_,3,r=T)1:(_,3,r=T)1 0.020 0.023 0.092
p(_,3,r=T)2:(_,3,r=T)1 0.021 0.017 0.041 0.394
p(_,3,r=T)3:(_,3,r=T)1 -0.048 -0.050 0.000 0.534 0.022
p(_,3,r=T)1:(_,3,r=T)2 0.026 0.010 0.042 0.418 0.990 0.052
p(_,3,r=T)2:(_,3,r=T)2 -0.041 -0.040 0.007 0.594 0.018 0.921
p(_,3,r=T)3:(_,3,r=T)2 -0.038 0.031 0.001 0.036 0.071 -0.074
p(_,3,r=T)1:(_,3,r=T)3 -0.039 -0.024 0.007 0.536 0.022 0.846
p(_,3,r=T)2:(_,3,r=T)3 -0.039 0.013 -0.005 0.069 0.022 -0.085
p(_,3,r=T)3:(_,3,r=T)3 0.026 -0.023 -0.009 0.143 -0.055 -0.063
p(_,3,r=T)1:(_,3,r=T)2 p(_,3,r=T)2:(_,3,r=T)2 p(_,3,r=T)3:(_,3,r=T)2 p(_,3,r=T)1:(_,3,r=T)3
ply(c_,3,r=T)1
ply(c_,3,r=T)2
ply(c_,3,r=T)3
ply(g_,3,r=T)1
ply(g_,3,r=T)2
ply(g_,3,r=T)3
ctd_c
dropoutaliv
obs_c
p(_,3,r=T)1:(_,3,r=T)1
p(_,3,r=T)2:(_,3,r=T)1
p(_,3,r=T)3:(_,3,r=T)1
p(_,3,r=T)1:(_,3,r=T)2
p(_,3,r=T)2:(_,3,r=T)2 0.068
p(_,3,r=T)3:(_,3,r=T)2 0.064 0.090
p(_,3,r=T)1:(_,3,r=T)3 0.067 0.948 0.282
p(_,3,r=T)2:(_,3,r=T)3 0.065 0.174 0.839 0.313
p(_,3,r=T)3:(_,3,r=T)3 0.017 0.199 -0.164 0.049
p(_,3,r=T)2:(_,3,r=T)3
ply(c_,3,r=T)1
ply(c_,3,r=T)2
ply(c_,3,r=T)3
ply(g_,3,r=T)1
ply(g_,3,r=T)2
ply(g_,3,r=T)3
ctd_c
dropoutaliv
obs_c
p(_,3,r=T)1:(_,3,r=T)1
p(_,3,r=T)2:(_,3,r=T)1
p(_,3,r=T)3:(_,3,r=T)1
p(_,3,r=T)1:(_,3,r=T)2
p(_,3,r=T)2:(_,3,r=T)2
p(_,3,r=T)3:(_,3,r=T)2
p(_,3,r=T)1:(_,3,r=T)3
p(_,3,r=T)2:(_,3,r=T)3
p(_,3,r=T)3:(_,3,r=T)3 0.314
> orth_c3_a3
Linear mixed model fit by REML ['lmerMod']
Formula: churchattendance ~ poly(cohort_c, 3) * poly(age_c, 3) + ctd_c + dropoutalive + obs_c + (1 + poly(age_c, 3) | PERSNR)
Data: long.kg
REML criterion at convergence: 317929.9
Random effects:
Groups Name Variance Std.Dev. Corr
PERSNR (Intercept) 5.829e-01 0.7635
poly(age_c, 3)1 6.205e+03 78.7731 0.609
poly(age_c, 3)2 1.195e+03 34.5631 -0.248 -0.919
poly(age_c, 3)3 1.074e+04 103.6105 0.037 0.240 -0.275
Residual 2.939e-01 0.5421
Number of obs: 152065, groups: PERSNR, 28984
Fixed effects:
Estimate Std. Error t value
(Intercept) 5.748e-01 8.503e-02 6.760
poly(cohort_c, 3)1 -4.726e+02 1.259e+02 -3.754
poly(cohort_c, 3)2 -2.298e+01 3.091e+01 -0.744
poly(cohort_c, 3)3 -6.297e+01 3.728e+01 -1.689
poly(age_c, 3)1 -4.936e+02 1.241e+02 -3.978
poly(age_c, 3)2 -2.091e+02 3.554e+01 -5.885
poly(age_c, 3)3 -1.418e+02 2.935e+01 -4.830
ctd_c -4.570e-02 5.068e-03 -9.017
dropoutalive 1.651e-02 1.063e-02 1.553
obs_c 1.452e-02 1.401e-03 10.364
poly(cohort_c, 3)1:poly(age_c, 3)1 -8.326e+04 2.016e+04 -4.130
poly(cohort_c, 3)2:poly(age_c, 3)1 -9.748e+04 3.296e+04 -2.957
poly(cohort_c, 3)3:poly(age_c, 3)1 -1.448e+04 4.802e+03 -3.016
poly(cohort_c, 3)1:poly(age_c, 3)2 -1.274e+05 3.051e+04 -4.174
poly(cohort_c, 3)2:poly(age_c, 3)2 -4.369e+04 7.859e+03 -5.559
poly(cohort_c, 3)3:poly(age_c, 3)2 -1.079e+04 1.905e+03 -5.662
poly(cohort_c, 3)1:poly(age_c, 3)3 -2.835e+04 4.084e+03 -6.942
poly(cohort_c, 3)2:poly(age_c, 3)3 -1.720e+04 1.604e+03 -10.727
poly(cohort_c, 3)3:poly(age_c, 3)3 -3.870e+03 5.176e+02 -7.477
Correlation of Fixed Effects:
(Intr) ply(c_,3)1 ply(c_,3)2 ply(c_,3)3 ply(g_,3)1 ply(g_,3)2 ply(g_,3)3 ctd_c drptlv obs_c p(_,3)1:(_,3)1
ply(ch_,3)1 0.227
ply(ch_,3)2 0.752 -0.436
ply(ch_,3)3 0.206 0.988 -0.456
ply(g_c,3)1 0.326 0.992 -0.340 0.970
ply(g_c,3)2 0.880 0.627 0.396 0.594 0.708
ply(g_c,3)3 0.334 0.971 -0.322 0.939 0.989 0.717
ctd_c -0.002 0.017 -0.019 0.009 0.018 0.004 0.020
dropoutaliv -0.082 0.028 -0.041 0.027 0.025 -0.016 0.012 0.044
obs_c 0.117 0.000 0.041 0.051 0.004 0.068 0.047 -0.039 -0.178
p(_,3)1:(_,3)1 0.983 0.176 0.796 0.150 0.276 0.867 0.285 -0.007 -0.032 0.064
p(_,3)2:(_,3)1 0.258 0.996 -0.409 0.987 0.991 0.651 0.971 0.010 0.021 0.041 0.207
p(_,3)3:(_,3)1 0.857 -0.009 0.860 -0.034 0.084 0.693 0.093 -0.038 -0.052 0.010 0.920
p(_,3)1:(_,3)2 0.320 0.987 -0.345 0.963 0.996 0.707 0.991 0.015 0.015 0.043 0.272
p(_,3)2:(_,3)2 0.869 -0.005 0.839 -0.035 0.092 0.731 0.107 -0.028 -0.039 0.014 0.938
p(_,3)3:(_,3)2 0.096 0.076 0.030 0.034 0.092 0.158 0.094 -0.062 0.026 -0.011 0.118
p(_,3)1:(_,3)3 0.847 -0.005 0.800 -0.036 0.091 0.730 0.110 -0.012 -0.024 0.012 0.916
p(_,3)2:(_,3)3 0.106 0.056 0.050 0.013 0.078 0.168 0.088 -0.077 0.023 -0.014 0.133
p(_,3)3:(_,3)3 0.096 -0.013 0.086 -0.028 0.005 0.116 0.021 0.039 -0.009 -0.020 0.128
p(_,3)2:(_,3)1 p(_,3)3:(_,3)1 p(_,3)1:(_,3)2 p(_,3)2:(_,3)2 p(_,3)3:(_,3)2 p(_,3)1:(_,3)3 p(_,3)2:(_,3)3
ply(ch_,3)1
ply(ch_,3)2
ply(ch_,3)3
ply(g_c,3)1
ply(g_c,3)2
ply(g_c,3)3
ctd_c
dropoutaliv
obs_c
p(_,3)1:(_,3)1
p(_,3)2:(_,3)1
p(_,3)3:(_,3)1 0.015
p(_,3)1:(_,3)2 0.992 0.078
p(_,3)2:(_,3)2 0.026 0.962 0.096
p(_,3)3:(_,3)2 0.139 0.045 0.154 0.162
p(_,3)1:(_,3)3 0.028 0.905 0.100 0.978 0.215
p(_,3)2:(_,3)3 0.115 0.061 0.143 0.192 0.942 0.253
p(_,3)3:(_,3)3 -0.006 0.110 0.020 0.232 0.128 0.214 0.238
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