estimate_magnitude function

Estimates for a continuous variable with no grouping (single-group design)

estimate_magnitude is suitable for a single group design with a continuous outcome variable. It estimates the population mean and population median (raw data only) with confidence intervals. You can pass raw data or summary data.

estimate_magnitude(
  data = NULL,
  outcome_variable = NULL,
  mean = NULL,
  sd = NULL,
  n = NULL,
  outcome_variable_name = "My outcome variable",
  conf_level = 0.95,
  save_raw_data = TRUE
)

Arguments

• data: For raw data - A data frame or tibble
• outcome_variable: For raw data - The column name of the outcome variable, or a vector of numeric data
• mean: For summary data - A numeric representing the mean of the outcome variable
• sd: For summary data - A numeric > 0, standard deviation of the outcome variable
• n: For summary data - An integer > 0, sample size of the outcome variable
• outcome_variable_name: Optional friendly name for the outcome variable. Defaults to 'My outcome variable' or the outcome variable column name if a data frame is passed.
• conf_level: The confidence level for the confidence interval. Given in decimal form. Defaults to 0.95.
• save_raw_data: For raw data; defaults to TRUE; set to FALSE to save memory by not returning raw data in estimate object

Returns

Returns an object of class esci_estimate

• overview

  • outcome_variable_name -
  • mean -
  • mean_LL -
  • mean_UL -
  • median -
  • median_LL -
  • median_UL -
  • sd -
  • min -
  • max -
  • q1 -
  • q3 -
  • n -
  • missing -
  • df -
  • mean_SE -
  • median_SE -

• es_mean

  • outcome_variable_name -
  • effect -
  • effect_size -
  • LL -
  • UL -
  • SE -
  • df -
  • ta_LL -
  • ta_UL -

• es_median

  • outcome_variable_name -
  • effect -
  • effect_size -
  • LL -
  • UL -
  • SE -
  • df -
  • ta_LL -
  • ta_UL -

• raw_data

  • grouping_variable -
  • outcome_variable -

Details

Reach for this function in place of a one-sample t-test or z-test.

Once you generate an estimate with this function, you can visualize it with plot_magnitude().

If you want to compare your sample to a known value or reference, then use estimate_mdiff_one().

The estimated mean is from statpsych::ci.mean1() (renamed ci.mean as of statpsych 1.6).

The estimated median is from statpsych::ci.median1() (renamed ci.median as of statpsych 1.6)

Examples

# From raw data
data("data_penlaptop1")

estimate_from_raw <- esci::estimate_magnitude(
  data = data_penlaptop1[data_penlaptop1$condition == "Pen", ],
    outcome_variable = transcription
)

# To visualize the estimate
myplot_from_raw <- esci::plot_magnitude(
  estimate_from_raw,
  effect_size = "median"
)

# From summary data
mymean <- 24.5
mysd <- 3.65
myn <- 40

estimate_from_summary <- esci::estimate_magnitude(
  mean = mymean,
  sd = mysd,
  n = myn
)

# To visualize the estimate
myplot_from_summary <- esci::plot_magnitude(
  estimate_from_summary,
  effect_size = "mean"
)