FSM (version 1.0.0)

love_plot: Love plot

Description

Generates a Love plot of Absolute Standardized Mean Differences (ASMD) or Target Absolute Standardized Differences (TASMD) between two groups under one or two designs.

Usage

love_plot(
  data_frame,
  index_col = TRUE,
  alloc1,
  alloc2 = NULL,
  imbalance = "TASMD",
  treat_lab = 1,
  vline = "",
  xupper = 1,
  mean_tar = NULL,
  sd_tar = NULL,
  denom = "target",
  legend_text = "FSM",
  legend_position = "topright"
)

Arguments

data_frame

Data frame containing a column of unit indices (optional) and covariates (or transformations thereof).

index_col

if TRUE, data_frame contains a column of unit indices.

alloc1

A vector of treatment assignment.

alloc2

A (optional) vector of treatment assignment.

imbalance

Measure of imbalance used. If imbalance = 'TASMD', imbalance is computed using the Target Absolute Standardized Mean Differences (TASMD). If imbalance = 'ASMD', imbalance is computed using the Absolute Standardized Mean Differences (ASMD)

treat_lab

Label of the treatment group in which the TASMD is computed. Applicable only when imbalance = 'TASMD'.

vline

A (optional) x-coordinate at which a vertical line is drawn.

xupper

Upper limit of the x-axis.

mean_tar

A (optional) vector of target profile of the covariates under consideration, e.g., mean of the covariates in the target population. Applicable only when imbalance = 'TASMD'. If mean_tar = NULL, the full-sample average of the covariates is considered as the target profile.

sd_tar

A optional vector of the standard deviation of the covariates in the target population. Applicable only when imbalance = 'TASMD'.

denom

Specifies the denominator for the computation of TASMD. If denom = 'target', the standard deviations of the covariates in the target population are used. If denom = 'group', the standard deviations of the covariates in the treatment group given by treat_lab are used. Applicable only when imbalance = 'TASMD'.

legend_text

Legend of the two designs under consideration.

legend_position

= Position of the legend in the plot. The default is 'topright'.

Value

Love plot of the ASMD/TASMD of the covariates.

References

Chattopadhyay, A., Morris, C. N., and Zubizarreta, J. R. (2020), ``Randomized and Balanced Allocation of Units into Treatment Groups Using the Finite Selection Model for R".

Love, T. (2004), <U+201C>Graphical display of covariate balance<U+201D>, Presentation, See http://chrp.org/love/JSM2004RoundTableHandout.pdf, 1364.

Examples

# NOT RUN {
# Consider the Lalonde dataset.
# Get the full sample size.
N = nrow(Lalonde)
# Get the treatment group sizes.
n1 = floor(N/2)
n2 = N-n1
# Generate an SOM.
som_obs = som(n_treat = 2, treat_sizes = c(n1,n2),include_discard = FALSE,
method = 'SCOMARS', marginal_treat = rep((n2/N),N), control = FALSE)
# Generate a treatment assignment given som_obs.
f = fsm(data_frame = Lalonde, SOM = som_obs, s_function = 'Dopt', eps = 0.0001, 
ties = 'random', intercept = TRUE, standardize = TRUE, units_print = FALSE)
# Get assignment vector under the FSM.
Z_fsm_obs = f$data_frame_allocated$Treat
# Draw a random CRD.
Z_crd_obs = crd(data_frame = Lalonde, n_treat = 2, treat_sizes = c(n1, n2), 
control = FALSE)$Treat
# Draw Love plot.
love_plot(data_frame = Lalonde, index_col = TRUE, alloc1 = Z_fsm_obs, alloc2 = Z_crd_obs, 
imbalance = 'TASMD', treat_lab = 1, mean_tar = NULL, sd_tar = NULL, denom = 'target',
vline = "", legend_text = c("FSM","CRD"), xupper = 0.15, legend_position = 'topright') 
# }