pump_power_grid {PUMP}

Run pump_power on varying values of parameters (grid function)

Description

This extension of 'pump_power()' will take lists of parameter values and run 'pump_power()' on all combinations of these values.

It can only assume the same MDES value for all outcomes due to this. (I.e., a vector of MDES values will be interpreted as a sequence of calls to pump_power, one for each MDES value given).

Each parameter in the parameter list can be a list, not scalar. It will cross all combinations of the list.

Usage

pump_power_grid(
  d_m,
  MTP = NULL,
  MDES,
  M = 1,
  nbar,
  J = 1,
  K = 1,
  propZero = NULL,
  numZero = NULL,
  Tbar,
  alpha = 0.05,
  numCovar.1 = NULL,
  numCovar.2 = NULL,
  numCovar.3 = NULL,
  R2.1 = NULL,
  R2.2 = NULL,
  R2.3 = NULL,
  ICC.2 = NULL,
  ICC.3 = NULL,
  omega.2 = NULL,
  omega.3 = NULL,
  rho = NULL,
  long.table = FALSE,
  verbose = FALSE,
  drop.unique.columns = TRUE,
  ...
)

Arguments

d_m

string; a single context, which is a design and model code. See pump_info() for list of choices.

MTP

string, or vector of strings; multiple testing procedure(s). See pump_info() for list of choices.

MDES

vector of numeric; This is *not* a list of MDES for each outcome, but rather a list of MDES to explore. Each value will be assumed held constant across all M outcomes.

M

scalar; the number of hypothesis tests (outcomes), including zero outcomes.

nbar

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.

J

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.

K

scalar; the number of level 3 units (districts).

propZero

Proportion of outcomes that have 0 impact (this will be used to override numZero, only one can be defined)

numZero

scalar; additional number of outcomes assumed to be zero. Please provide NumZero + length(MDES) = M, if length(MDES) is not 1.

Tbar

scalar; the proportion of samples that are assigned to the treatment.

alpha

scalar; the family wise error rate (FWER).

numCovar.1

scalar; number of level 1 (individual) covariates.

numCovar.2

scalar; number of level 2 (school) covariates.

numCovar.3

scalar; number of level 3 (district) covariates.

R2.1

scalar, or vector of length M; percent of variation explained by level 1 covariates for each outcome.

R2.2

scalar, or vector of length M; percent of variation explained by level 2 covariates for each outcome.

R2.3

scalar, or vector of length M; percent of variation explained by level 3 covariates for each outcome.

ICC.2

scalar, or vector of length M; level 2 (school) intraclass correlation.

ICC.3

scalar, or vector length M; level 3 (district) intraclass correlation.

omega.2

scalar, or vector of length M; ratio of variance of level 2 average impacts to variance of level 2 random intercepts.

omega.3

scalar, or vector of length M; ratio of variance of level 3 average impacts to variance of level 3 random intercepts.

rho

scalar; assumed correlation between all pairs of test statistics.

long.table

TRUE for table with power as rows, correction as columns, and with more verbose names. See 'transpose_power_table'.

verbose

logical; TRUE means print out some text as calls processed. FALSE do not.

drop.unique.columns

logical; drop all parameter columns that did not vary across the grid.

...

extra arguments passed to the underlying pump_power, pump_sample, or pump_mdes functions.

Value

a pumpgridresult object containing power results.

See Also

Other grid functions: pump_mdes_grid(), pump_sample_grid()

Examples

g <- pump_power_grid( d_m = "d3.2_m3ff2rc", MTP = c( "HO", "BF" ),
 MDES = 0.10, J = seq(5, 10, 1), M = 5, K = 7, nbar = 58,
 Tbar = 0.50, alpha = 0.15, numCovar.1 = 1,
 numCovar.2 = 1, R2.1 = 0.1, R2.2 = 0.7,
 ICC.2 = 0.25, ICC.3 = 0.25, rho = 0.4, tnum = 1000)