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Association Scatter Table

Source: R/Table_AssociationScatter.R
Table_AssociationScatter.Rd

The statistics of the view the association scatter opens on, as a table: for each panel, R's correlation coefficient and, when fit asks for one, its fitted line, each a row with its method, estimates and intervals, counts, p-value and note, written as the chart prints them. The numbers are Analyze_Correlation()'s and Analyze_Fit()'s on the rows the chart draws.

Usage

Table_AssociationScatter(dfResults, dfParticipants = NULL, lSettings = list())

Arguments

dfResults

data.frame Long-format results, one row per participant, biomarker and visit. Column names are supplied by lSettings; the defaults expect USUBJID/TEST/STRESN/VISIT/VISITNUM/STRESU, the columns of Synthetic_Results.

dfParticipants

data.frame One row per participant, or NULL. With it the chart has filters, offers its category columns to colour and panel by and its numeric columns on either axis; it also says who the participants are. Without it a colour or a number comes from a column carried on the results rows. Default: NULL.

lSettings

list bio.viz association scatter settings, as Widget_AssociationScatter() takes them, and title, subtitle and footnotes. Default: list().

Value

A data.frame of text: Panel with panel_by, then Statistic, Method, Estimate, Counts, p-value and Note, with the attributes of Table_GroupComparison().

Titles and footnotes

As for Visualize_AssociationScatter(): {x}, {y}, {n}, {filters}, {date} and {version}.

Display rules

A p-value is written to three decimals, p < 0.001 below that and p > 0.999 above, never with stars. Every row is labelled exploratory, with its adjustment named when it has one. An estimate is written to four significant digits with its confidence interval. A statistic R did not compute has no p-value, and its note is R's reason.

See also

Visualize_AssociationScatter() and Widget_AssociationScatter().

Other tables: Table_BiomarkerScreen(), Table_CorrelationMatrix(), Table_CrossTab(), Table_GroupComparison(), Table_StratifiedSurvival(), Write_RTF()

Examples

Table_AssociationScatter(
  Synthetic_Results,
  Synthetic_Participants,
  lSettings = list(
    x = list(measure = "TNF-alpha", visit = "Baseline"),
    y = list(measure = "IL-10", visit = "Baseline"),
    fit = "linear"
  )
)
#>     Statistic                               Method
#> 1 Correlation Pearson's product-moment correlation
#> 2 Fitted line                    Linear regression
#>                                                                                                                             Estimate
#> 1                                                                      Pearson’s r: 0.6384, 95% confidence interval 0.5482 to 0.7139
#> 2 Slope: 0.3275, 95% confidence interval 0.2721 to 0.3828; Intercept: 2.028, 95% confidence interval 1.356 to 2.7; R-squared: 0.4075
#>    Counts   p-value                     Note
#> 1 n = 200 p < 0.001 Exploratory, unadjusted.
#> 2 n = 200 p < 0.001 Exploratory, unadjusted.