The output looks like this:

HTML:

```
Call:
mlogit(RES ~ Money + X1a + X1b + X2a + X2b | Age,
data = CE, reflevel = "C", shape = "long", alt.var = "ALT", method = "nr",
print.level = 0)
Frequencies of alternatives:
C A B
0.56206 0.22340 0.21454
nr method
5 iterations, 0h:0m:1s
g'(-H)^-1g = 1.09E-07
gradient close to zero
Coefficients :
Estimate Std. Error t-value Pr(>|t|)
A:(intercept) 0.9541021 0.3779952 2.5241 0.0115991 *
B:(intercept) 1.0174949 0.4033790 2.5224 0.0116547 *
X1a -0.7386523 0.1960883 -3.7669 0.0001653 ***
X1b -2.1118971 0.2563337 -8.2389 2.220e-16 ***
X1a -1.0645459 0.2822902 -3.7711 0.0001625 ***
X2b -3.3511706 0.3283743 -10.2053 < 2.2e-16 ***
Money 0.0102814 0.0028901 3.5574 0.0003745 ***
A:Age 0.8188962 0.1400442 5.8474 4.993e-09 ***
B:Age 0.5245825 0.1287723 4.0737 4.627e-05 ***
---
```

**Problem: I want only one single intercept and only one single variable Age instead of one intercept and one Age variable for each alternative A and B.**

The Method:

- In the experiment, persons of different age (=alternative-invariant variable) had to fill out two choice sets. In each choice set, the person had to choose between three alternatives: A, B, and C (=reference).

- Each alternative has three attributes (alternative-variant variables): X1, X2, and Money.

- Each of the attributes has two levels, denoted "a" and "b", or a number for the monetary attribute.

**Question: How do I restrict the coefficient for my alternative invariant variable ("Age") to be equal for alternative A and B?**

The long format of the data looks like this:

Note: ALT = Alternative (A, B, or C); QES = number of choice set; RES = Choice of the person; X1a, X1b, X2a, X2b = Alternative-variant variables; Age = Alternative-invariant variable

A reviewer suggested this for my paper. Can someone help?