Hello R users,
I am performing a multinomial logit regression and would like to
constrain a few model coefficients to be equal.
Here is my model:
multi <- vglm(case123con ~ SNP_A1+SNP_A2+age, multinomial, work.analy)
where case123con is a four level categorical variable (case 1, case 2,
case 3, control) and SNP_A1 and SNP_A2 are indicator functions (yes/no).
The output of this model is:
Coefficients:
Value Std. Error t value
(Intercept):1 6.9798044 0.8145521 8.5688866
(Intercept):2 2.5729346 0.8733182 2.9461592
(Intercept):3 0.0129745 1.0966651 0.0118308
age:1 -0.0468339 0.0087766 -5.3362053
age:2 -0.0306066 0.0091644 -3.3397314
age:3 -0.0058718 0.0114316 -0.5136443
SNP_A1:1 0.0284303 0.1590333 0.1787698
SNP_A1:2 0.1685160 0.1674925 1.0061104
SNP_A1:3 0.0137997 0.2052559 0.0672315
SNP_A2:1 -0.6265717 0.2694583 -2.3253010
SNP_A2:2 -0.2528873 0.2790632 -0.9062006
SNP_A2:3 -0.0789181 0.3339153 -0.2363418
I would like to constrain the model coefficients so that SNP_A1:1 =
SNP_A1:2 = SNP_A1:3 and SNP_A2:1 = SNP_A2:2 = SNP_A2:3. The reason I
want to do this is because I want to test the null hypothesis that these
coefficients are equal through a likelihood ratio test. Can I do this
by defining the constraint matrices and if so, how do I go about doing
so?
Any help or tips would be greatly appreciated! Thank you in advance!!
Lin
**NOTA DE CONFIDENCIALIDAD** Este correo electrÿnico, ...{{dropped:18}}
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