### Question about the re-coded level-1 variables

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**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

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 511.57278RP3_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