calc_BCSMD.RdIn one call, 1) clean single-case design data for treatment reversal and multiple baseline designs, 2) fit a multi-level model using restricted maximum likelihood estimation, and 3) estimate a standardized mean difference effect size.
calc_BCSMD(
design,
case,
phase,
session,
outcome,
cluster = NULL,
series = NULL,
center = 0,
round_session = TRUE,
treatment_name = NULL,
FE_base = 0,
RE_base = 0,
RE_base_2 = NULL,
FE_trt = 0,
RE_trt = NULL,
RE_trt_2 = NULL,
corStruct = "AR1",
varStruct = "hom",
A = NULL,
B = NULL,
D = NULL,
cover = 95,
bound = 35,
symmetric = TRUE,
summary = TRUE,
data = NULL,
...
)Character string to specify whether data comes from a treatment
reversal ("TR"), multiple baseline across participants
("MBP"), replicated multiple baseline across behaviors
("RMBB"), or clustered multiple baseline across participants
("CMB").
vector of case indicators or name of a character or factor vector
within data indicating unique cases.
vector of treatment indicators or name of a character or factor
vector within data indicating unique treatment phases.
vector of measurement occasions or name of numeric vector
within data of measurement times.
vector of outcome data or name of numeric vector of outcome
data within data.
(Optional) vector of cluster indicators or name of a character
or factor vector within data indicating clusters.
(Optional) vector of series indicators or name of a character
or factor vector within data indicating series.
Numeric value for the centering value for session. Default is 0.
Logical indicating whether to round session to the nearest integer. Defaults to TRUE.
(Optional) character string corresponding to the name of the treatment phase.
Vector of integers specifying which fixed effect terms to
include in the baseline phase. Setting FE_base = 0 includes only a
level. Setting FE_base = c(0,1) includes a level and a linear time
trend.
Vector of integers specifying which random effect terms to
include in the baseline phase. Setting RE_base = 0 includes only
levels (i.e., random intercepts). Setting RE_base = c(0,1) includes
random levels and random linear trends.
Vector of integers specifying which random effect terms to
include in the baseline phase for the cluster level in clustered multiple
baseline design across participants or for the case level in replicated
multiple baseline across behaviors. Setting RE_base_2 = 0 includes
only levels (i.e., random intercepts). Setting RE_base_2 = c(0,1)
includes random levels and random linear trends.
Vector of integers specifying which fixed effect terms to
include in the treatment phase. Setting FE_trt = 0 includes only a
change in level. Setting FE_trt = c(0,1) includes a change in level
and a treatment-by-linear time trend.
Vector of integers specifying which random effect terms to
include in the treatment phase. Setting RE_trt = 0 includes only
random changes in level. Setting RE_trt = c(0,1) includes random
changes in level and random treatment-by-linear time trends.
Vector of integers specifying which random effect terms to
include in the treatment phase for the cluster level in clustered multiple
baseline design across participants or for the case level in replicated
multiple baseline across behaviors. Setting RE_trt_2 = 0 includes
only random changes in level. Setting RE_trt_2 = c(0,1) includes
random changes in level and random treatment-by-linear time trends.
(Optional) character string indicating the correlation
structure of session-level errors. Options are "AR1" (default),
"MA1", or "IID".
(Optional) character string indicating the
heteroscedasticity structure of session-level errors. Options are
"hom" (default) or "het", which allows for the session-level
error variances to differ by phase.
The time point immediately before the start of treatment in the hypothetical between-group design.
The time point at which outcomes are measured in the hypothetical between-group design.
Numerical indicating the treatment duration across cases. Note that
B = A + D and it is not allowed to specify both B and
D.
Confidence level.
Numerical tolerance for non-centrality parameter in
qt.
If TRUE (the default), use a symmetric confidence
interval. If FALSE, use a non-central t approximation to obtain an
asymmetric confidence interval.
Logical indicating whether to return a data frame with effect
size estimates and other information. If TRUE (default), return a
data.frame containing the effect size estimate, standard error,
confidence interval, and other information. If FALSE, return a list
with effect size estimate, degrees of freedom, and other information.
(Optional) dataset to use for analysis. Must be a
data.frame.
further arguments.
If summary == TRUE, a data frame containing the
design-comparable effect size estimate, standard error, confidence
interval, and other information. If summary == FALSE, a list
containing all elements of a `g_mlm()` object, plus the fitted `lme()`
model.
data(Laski)
# Change-in-levels model with fixed treatment effect
calc_BCSMD(design = "MBP",
case = case, phase = treatment,
session = time, outcome = outcome,
FE_base = 0, RE_base = 0, FE_trt = 0,
data = Laski)
#> BC-SMD estimate Std. Error 95% CI (lower) 95% CI (upper) Degrees of freedom
#> 1 1.404887 0.2863249 0.8046221 2.005152 18.5524
#> Auto-correlation Variance parameter Intra-class correlation
#> 1 0.2527692 NA 0.5606065
#> Initial treatment time Follow-up time Converged
#> 1 4 13 Yes
# Model with linear time trends in baseline and treatment phases,
# random baseline slopes, fixed treatment effects
calc_BCSMD(design = "MBP",
case = case, phase = treatment,
session = time, outcome = outcome, center = 4,
FE_base = c(0,1), RE_base = c(0,1),
FE_trt = c(0,1),
data = Laski)
#> Warning: nlminb problem, convergence error code = 1
#> message = iteration limit reached without convergence (10)
#> BC-SMD estimate Std. Error 95% CI (lower) 95% CI (upper) Degrees of freedom
#> 1 1.885295 0.5846749 0.675189 3.0954 22.79118
#> Auto-correlation Variance parameter Intra-class correlation
#> 1 0.1313209 NA 0.7188766
#> Initial treatment time Follow-up time Converged
#> 1 4 13 No
data(Anglesea)
calc_BCSMD(design = "TR",
case = case, phase = condition,
session = session, outcome = outcome,
treatment_name = "treatment",
FE_base = 0, RE_base = 0,
FE_trt = 0,
data = Anglesea)
#> BC-SMD estimate Std. Error 95% CI (lower) 95% CI (upper) Degrees of freedom
#> 1 1.490965 0.9876571 -1.470357 4.452286 3.359203
#> Auto-correlation Variance parameter Intra-class correlation
#> 1 0.4978687 NA 0.7260842
#> Initial treatment time Follow-up time Converged
#> 1 NA NA Yes
data(Thiemann2001)
calc_BCSMD(design = "RMBB",
case = case, series = series, phase = treatment,
session = time, outcome = outcome,
FE_base = 0, RE_base = 0, RE_base_2 = 0,
FE_trt = 0,
data = Thiemann2001)
#> BC-SMD estimate Std. Error 95% CI (lower) 95% CI (upper) Degrees of freedom
#> 1 1.598701 0.1803463 1.239027 1.958375 70.16912
#> Auto-correlation Variance parameter Intra-class correlation
#> 1 0.19949 NA Level2:0.322 Level3:0.109
#> Initial treatment time Follow-up time Converged
#> 1 9 15 Yes
data(Bryant2018)
calc_BCSMD(design = "CMB",
cluster = group, case = case, phase = treatment,
session = session, outcome = outcome, center = 49,
treatment_name = "treatment",
FE_base = c(0,1), RE_base = 0, RE_base_2 = 0,
FE_trt = c(0,1), RE_trt = NULL, RE_trt_2 = NULL,
data = Bryant2018)
#> BC-SMD estimate Std. Error 95% CI (lower) 95% CI (upper) Degrees of freedom
#> 1 -2.245586 0.5876192 -3.425588 -1.065584 50.45912
#> Auto-correlation Variance parameter Intra-class correlation
#> 1 0.6305068 NA Level2:0.771 Level3:0
#> Initial treatment time Follow-up time Converged
#> 1 5 54 Yes