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exponential growth, separate packages

Usage

rfeat(
  tumr_obj = NULL,
  data = NULL,
  id = NULL,
  time = NULL,
  measure = NULL,
  group = NULL,
  log = TRUE,
  comparison = c("t.test", "anova", "tukey", "both")
)

Arguments

tumr_obj

takes tumr_obj created by tumr()

data

From gendat

id

Column of subject ID's

time

Column of repeated time measurements

measure

Column of repeated measurements of tumor

group

Column specifying the treatment group for each measurement

log

log transformation of measurement using log1p

comparison

Takes "t.test", "anova", "tukey", or "both"

Value

A p-value

Examples

data(breast)
rfeat(
data = breast,
id = "ID",
time = "Week",
measure = "Volume",
group = "Treatment",
comparison = "t.test")
#> 
#> 	Welch Two Sample t-test
#> 
#> data:  Beta by Group
#> t = 0.64605, df = 24.351, p-value = 0.5243
#> alternative hypothesis: true difference in means between group NR and group VEH is not equal to 0
#> 95 percent confidence interval:
#>  -0.3345751  0.6398147
#> sample estimates:
#>  mean in group NR mean in group VEH 
#>         0.8872739         0.7346541 
#> 
data(melanoma1)
rfeat(
data = melanoma1,
id = "ID",
time = "Day",
measure = "Volume",
group = "Treatment",
comparison = "anova")
#>             Df  Sum Sq  Mean Sq F value   Pr(>F)    
#> Group        3 0.04132 0.013775    26.4 1.13e-08 ***
#> Residuals   31 0.01618 0.000522                     
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1