Description Usage Arguments Details Value See Also Examples
Returns a list with the current model parameter estimates
1 | summary_sema(x)
|
x |
A sema model output. |
The output of the sema_fit functions are usually large, and
difficult to read, lists. In order to interpret the output of the sema_fit
functions, summary_sema
returns a general overview of the model
parameters, the fixed effects coefficients, the random effects variances
and covariances, and the residual variance. The summary_sema
function is also incorpprated within the sema_fit_one
function,
such that with the argument print_every
the user can see a summary
of the updated model parameters every X data points.
A list with sample size, number of units, the coefficients of the fixed effects, the variance of the random effects and the residual variance.
store_fixed_coef
,
store_random_var
, store_resid_var
,
ranef
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ## First we create a dataset, consisting of 2500 observations from 20
## units. The fixed effects have the coefficients 1, 2, 3, 4, and 5. The
## variance of the random effects equals 1, 4, and 9. Lastly the
## residual variance equals 4:
test_data <- build_dataset(n = 2500,
j = 20,
fixed_coef = 1:5,
random_coef_sd = 1:3,
resid_sd = 2)
## Next, we fit a simple model to these data
m1 <- sema_fit_df(formula = y ~ 1 + V3 + V4 + V5 + V6 + (1 + V4 + V5 | id),
data_frame = test_data,
intercept = TRUE)
summary_sema(m1)
|
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