make_rho: Build the item-response probability matrix for the simulation
In tseLCA: Three-Step Estimation for Latent Class Analysis
make_rho R Documentation
Build the item-response probability matrix for the simulation
Description
Returns a T x K matrix rho where rho[t, k] = P(Y_k = 1 | X = t).
Usage
make_rho(pi_)
Arguments
pi_
Numeric scalar in (0.5, 1). Probability of the "likely" response.
Use bk2018_params$separation_levels for the three simulation levels.
Details
The three-class structure is:
Class 1: pi_ on all 6 items (high responders).
Class 2: pi_ on items 1-3, 1 - pi_ on items 4-6 (mixed).
Class 3: 1 - pi_ on all 6 items (low responders).
Value
A 3 x 6 numeric matrix.
Examples
# High separation: P(Y=1|class) = 0.9 for the "high" class
make_rho(0.9)
# Low separation
make_rho(0.7)
tseLCA documentation built on Nov. 11, 2026, 9:07 a.m.
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| make_rho | R Documentation |
Build the item-response probability matrix for the simulation
Description
Returns a T x K matrix rho where rho[t, k] = P(Y_k = 1 | X = t).
Usage
make_rho(pi_)
Arguments
pi_ |
Numeric scalar in (0.5, 1). Probability of the "likely" response.
Use |
Details
The three-class structure is:
Class 1:
pi_on all 6 items (high responders).Class 2:
pi_on items 1-3,1 - pi_on items 4-6 (mixed).Class 3:
1 - pi_on all 6 items (low responders).
Value
A 3 x 6 numeric matrix.
Examples
# High separation: P(Y=1|class) = 0.9 for the "high" class
make_rho(0.9)
# Low separation
make_rho(0.7)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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