predict_with_observations_plot

Description

Plots predictions of the model with observed values

Usage

predict_with_observations_plot(
  data,
  fit,
  conc_col,
  dv_col,
  id_col = NULL,
  ntime_col = NULL,
  trt_col = NULL,
  treatment_predictors,
  control_predictors = NULL,
  reference_threshold = c(
  10
),
  conf_int = 0.9,
  contrast_method = c(
  "matched",
  "group"
),
  style = list(
)
)

Arguments

Name	Description
data	a dataframe of QTc dataset
fit	the lme model to make predictions with
conc_col	an unquoted column name of drug concentration measurements
dv_col	an unquoted column name of dQTC measurements
id_col	an unquoted column name of ID data, used when control predictors is provided to compute delta delta dv
ntime_col	an unquoted column name of Nominal time data, used when control predictors is provided to compute delta delta dv
trt_col	an unquoted column name of Treatment group data, used when control predictors is provided to compute delta delta dv
treatment_predictors	a list for predictions with model. Should contain a value for each predictor in the model.
control_predictors	an optional list for contrast predictions
reference_threshold	optional vector of numbers to add as horizontal dashed lines
conf_int	a float for the fractional confidence interval. default = 0.9
contrast_method	a string specifying contrast method when using control_predictors: “matched” for individual ID+time matching (crossover studies), “group” for group-wise subtraction (parallel studies)
style	a named list of any argument that can be passed to style_plot

Returns

a plot

Examples

data <- preprocess(data)
 fit <- fit_prespecified_model(
   data,
   deltaQTCF,
   ID,
   CONC,
   deltaQTCFBL,
   TRTG,
   TAFD,
   "REML",
   TRUE
 )
 predict_with_observations_plot(
   data,
   fit,
   CONC,
   deltaQTCF,
   treatment_predictors = list(
     CONC = 0,
     TRTG = "Verapamil HCL",
     TAFD = "2 HR",
     deltaQTCFBL = 0
   ),
   conf_int = 0.9
 )