love_plot {FSM}

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.

Author(s)

Ambarish Chattopadhyay, Carl N. Morris and Jose R. Zubizarreta.

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), “Graphical display of covariate balance”, Presentation, See http://chrp.org/love/JSM2004RoundTableHandout.pdf, 1364.

Examples

# 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')