The user chooses the context (d_m), MTP, power definition, and choices of all relevant design parameters.
The functions performs a search algorithm, and returns the MDES value within the specified tolerance. For a list of choices for specific parameters, see pump_info().
pump_mdes(
d_m,
MTP = NULL,
numZero = NULL,
propZero = NULL,
M = 1,
nbar,
J = 1,
K = 1,
Tbar,
alpha = 0.05,
two.tailed = TRUE,
target.power = 0.8,
power.definition,
tol = 0.02,
numCovar.1 = 0,
numCovar.2 = 0,
numCovar.3 = 0,
R2.1 = 0,
R2.2 = 0,
R2.3 = 0,
ICC.2 = 0,
ICC.3 = 0,
omega.2 = 0,
omega.3 = 0,
rho = NULL,
rho.matrix = NULL,
B = 1000,
max.steps = 20,
tnum = 1000,
start.tnum = round(tnum/10),
final.tnum = 4 * tnum,
parallel.WY.cores = 1,
updateProgress = NULL,
give.optimizer.warnings = FALSE,
verbose = FALSE
)a pumpresult object containing MDES results.
string; a single context, which is a design and model code. See pump_info() for list of choices.
string, or vector of strings; multiple testing procedure(s). See pump_info() for list of choices.
scalar; additional number of outcomes assumed to be zero. Please provide NumZero + length(MDES) = M, if length(MDES) is not 1.
scalar; proportion of outcomes assumed to be zero (alternative specification to numZero). length(MDES) should be 1 or equal to (1-propZero)*M.
scalar; the number of hypothesis tests (outcomes), including zero outcomes.
scalar; the harmonic mean of the number of level 1 units per level 2 unit (students per school). Note that this is not the total number of level 1 units, but instead the number of level 1 units nested within each level 2 unit, so the total number of level 1 units is nbar x J x K.
scalar; the harmonic mean of number of level 2 units per level 3 unit (schools per district). Note that this is not the total number of level 2 units, but instead the number of level 2 units nested within each level 3 unit, so the total number of level 2 units is J x K.
scalar; the number of level 3 units (districts).
scalar; the proportion of samples that are assigned to the treatment.
scalar; the family wise error rate (FWER).
scalar; TRUE/FALSE for two-tailed or one-tailed power calculation.
target power for search algorithm.
see pump_info() for possible power definitions.
tolerance for target power, defaults to 0.01 (1 This parameter controls when the search is done: when estimated power (checked with `final.tnum` iterations) is within `tol`, the search stops.
scalar; number of level 1 (individual) covariates.
scalar; number of level 2 (school) covariates.
scalar; number of level 3 (district) covariates.
scalar, or vector of length M; percent of variation explained by level 1 covariates for each outcome.
scalar, or vector of length M; percent of variation explained by level 2 covariates for each outcome.
scalar, or vector of length M; percent of variation explained by level 3 covariates for each outcome.
scalar, or vector of length M; level 2 (school) intraclass correlation.
scalar, or vector length M; level 3 (district) intraclass correlation.
scalar, or vector of length M; ratio of variance of level 2 average impacts to variance of level 2 random intercepts.
scalar, or vector of length M; ratio of variance of level 3 average impacts to variance of level 3 random intercepts.
scalar; assumed correlation between all pairs of test statistics.
matrix; alternate specification allowing a full matrix of correlations between test statistics. Must specify either rho or rho.matrix, but not both.
scalar; the number of permutations for Westfall-Young procedures.
how many steps allowed before terminating.
max number of samples for first iteration of search algorithm.
number of samples to start search (this will increase with each step).
number of samples for final draw.
number of cores to use for parallel processing of WY-SD.
function to update progress bar (only used for PUMP shiny app).
whether to return verbose optimizer warnings.
TRUE/FALSE; Print out diagnostics of time, etc.
For more detailed information about this function and the user choices, see the manuscript <doi:10.18637/jss.v108.i06>, which includes a detailed Technical Appendix including information about the designs and models and parameters.
mdes <- pump_mdes(
d_m = "d3.1_m3rr2rr",
MTP = 'HO',
power.definition = 'D1indiv',
target.power = 0.6,
J = 30,
K = 15,
nbar = 50,
M = 3,
Tbar = 0.5, alpha = 0.05,
two.tailed = FALSE,
numCovar.1 = 1, numCovar.2 = 1,
R2.1 = 0.1, R2.2 = 0.1,
ICC.2 = 0.2, ICC.3 = 0.2,
omega.2 = 0.1, omega.3 = 0.1,
rho = 0.5, tnum = 2000)
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