Description Usage Arguments Details See Also
Input simulation conditions and which term to compute power for, export reported power.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28  sim_pow_single(
fixed,
fixed_param,
cov_param,
n,
error_var,
with_err_gen,
arima = FALSE,
data_str,
cor_vars = NULL,
fact_vars = list(NULL),
lvl1_err_params = NULL,
arima_mod = list(NULL),
contrasts = NULL,
homogeneity = TRUE,
heterogeneity_var = NULL,
knot_args = list(NULL),
missing = FALSE,
missing_args = list(NULL),
pow_param = NULL,
alpha,
pow_dist = c("z", "t"),
pow_tail = c(1, 2),
lm_fit_mod = NULL,
general_mod = NULL,
general_extract = NULL,
...
)

fixed 
One sided formula for fixed effects in the simulation. To suppress intercept add 1 to formula. 
fixed_param 
Fixed effect parameter values (i.e. beta weights). Must be same length as fixed. 
cov_param 
List of arguments to pass to the continuous generating function, must be the same order as the variables specified in fixed. This list does not include intercept, time, factors, or interactions. Required arguments include:
Optional arguments to the distribution functions are in a nested list, see the examples or vignettes for example code. 
n 
Cluster sample size. 
error_var 
Scalar of error variance. 
with_err_gen 
Simulated within cluster error distribution. Must be a quoted 'r' distribution function. 
arima 
TRUE/FALSE flag indicating whether residuals should
be correlated. If TRUE, must specify a valid model to pass to
arima.sim via the arima_mod argument.
See 
data_str 
Type of data. Must be "cross", "long", or "single". 
cor_vars 
A vector of correlations between variables. 
fact_vars 
A nested list of factor, categorical, or ordinal variable specification, each list must include:
Optional arguments include:
See also 
lvl1_err_params 
Additional parameters passed as a list on to the level one error generating function 
arima_mod 
A list indicating the ARIMA model to pass to arima.sim.
See 
contrasts 
An optional list that specifies the contrasts to be used
for factor variables (i.e. those variables with .f or .c).
See 
homogeneity 
Either TRUE (default) indicating homogeneity of variance assumption is assumed or FALSE to indicate desire to generate heterogeneity of variance. 
heterogeneity_var 
Variable name as a character string to use for heterogeneity of variance simulation. 
knot_args 
A nested list of named knot arguments. See

missing 
TRUE/FALSE flag indicating whether missing data should be simulated. 
missing_args 
Additional missing arguments to pass to the missing_data
function. See 
pow_param 
Name of variable to calculate power for, must be a name from fixed. 
alpha 
What should the per test alpha rate be used for the hypothesis testing. 
pow_dist 
Which distribution should be used when testing hypothesis test, z or t? 
pow_tail 
Onetailed or twotailed test? 
lm_fit_mod 
Valid lm syntax to be used for model fitting. 
general_mod 
Valid model syntax. This syntax can be from any R package. By default, broom is used to extract model result information. Note, package must be defined or loaded prior to running the sim_pow function. 
general_extract 
A valid function to extract model results if general_mod argument is used. This argument is primarily used if extracting model results is not possibly using the broom package. If this is left NULL (default), broom is used to collect model results. 
... 
Additional specification needed to pass to the random generating function defined by with_err_gen. 
Power function to compute power for a regression term for simple regression
models. This function would need to be replicated to make any statement about
power. Use sim_pow
as a convenient wrapper for this.
sim_pow
for a wrapper to replicate.
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