Question about the re-coded level-1 variables
Posted: Fri Oct 20, 2017 7:38 am
Dear,
Hello, I have a problem with the output of a binary model in R2MLwiN. I have recoded an ordered level-1 variable (1<2<3<4) and input it for a three level binary model using MCMC. In the output, it only shows the coefficient of its reference level but not of other three levels as for unordered categorical variables. Just wander why this happened and how to explain it if it is right. I have listed the results for your reference. Many thanks.
> r_temp.df$coef
est se stat p lwr upr ess
FP_Intercept -1.2461333 2.677351e-01 -4.6543512 3.250025e-06 -1.762658028 -0.7756006 73.06440
FP_Age_15-24 -0.1464940 3.333534e-01 -0.4394556 6.603315e-01 -0.829658486 0.4840200 511.57278
RP3_var_Intercept 0.2920189 5.101553e-01 0.5724117 5.670431e-01 0.001720491 1.7420080 45.11112
RP2_var_Intercept 3.9726860 9.247642e-01 4.2958908 1.739932e-05 2.442040654 6.0415510 368.77411
RP1_var_bcons_1 0.9999998 1.414214e-05 70710.6639765 0.000000e+00 1.000000000 1.0000000 5000.00000
> result_b2.df[[1]]$contrasts
$Age.f
.L .Q .C
1 -0.6708204 0.5 -0.2236068
2 -0.2236068 -0.5 0.6708204
3 0.2236068 -0.5 -0.6708204
4 0.6708204 0.5 0.2236068
Regards.
Diva
Hello, I have a problem with the output of a binary model in R2MLwiN. I have recoded an ordered level-1 variable (1<2<3<4) and input it for a three level binary model using MCMC. In the output, it only shows the coefficient of its reference level but not of other three levels as for unordered categorical variables. Just wander why this happened and how to explain it if it is right. I have listed the results for your reference. Many thanks.
> r_temp.df$coef
est se stat p lwr upr ess
FP_Intercept -1.2461333 2.677351e-01 -4.6543512 3.250025e-06 -1.762658028 -0.7756006 73.06440
FP_Age_15-24 -0.1464940 3.333534e-01 -0.4394556 6.603315e-01 -0.829658486 0.4840200 511.57278
RP3_var_Intercept 0.2920189 5.101553e-01 0.5724117 5.670431e-01 0.001720491 1.7420080 45.11112
RP2_var_Intercept 3.9726860 9.247642e-01 4.2958908 1.739932e-05 2.442040654 6.0415510 368.77411
RP1_var_bcons_1 0.9999998 1.414214e-05 70710.6639765 0.000000e+00 1.000000000 1.0000000 5000.00000
> result_b2.df[[1]]$contrasts
$Age.f
.L .Q .C
1 -0.6708204 0.5 -0.2236068
2 -0.2236068 -0.5 0.6708204
3 0.2236068 -0.5 -0.6708204
4 0.6708204 0.5 0.2236068
Regards.
Diva