R Under development (unstable) (2026-01-24 r89326 ucrt) -- "Unsuffered Consequences"
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> # This file is part of the statuser package
> # 
> # This file is run automatically by R CMD check
> library(testthat)
> library(statuser)
> 
> test_check("statuser")

statuser::clear()
Cleared console, plot, and environment
statuser::clear()
Cleared console, plot, and environment
desc_var() says:
Multiple grouping variables should not overlap perfectly: 'x1' and 'x2' overlap perfectly
Robin Hood calculations (see Simonsohn, 2018)
Explaining why x = 0.05 is used as the breakpoint

Most extreme value of fitted 'y' with GAM obtained at 'x' = 0.01
Local range of values considered for breakpoint 'x': [-0.33, 0.36]
t-values for two lines at 'x' = 0.01:
   t1 = 6.5
   t2 = 9.35
We compute t2/(t1+t2) = 0.59
We then lookup the value of 'x' at that quantile, so we run
quantile(x, 0.59) = 0.05 and set that value, 0.05, as the breakpoint.

Note: you may turn off this message by setting `quiet=TRUE`
Robin Hood calculations (see Simonsohn, 2018)
Explaining why x = 0.05 is used as the breakpoint

Most extreme value of fitted 'y' with GAM obtained at 'x' = 0.01
Local range of values considered for breakpoint 'x': [-0.33, 0.36]
t-values for two lines at 'x' = 0.01:
   t1 = 6.5
   t2 = 9.35
We compute t2/(t1+t2) = 0.59
We then lookup the value of 'x' at that quantile, so we run
quantile(x, 0.59) = 0.05 and set that value, 0.05, as the breakpoint.

Note: you may turn off this message by setting `quiet=TRUE`
Robin Hood calculations (see Simonsohn, 2018)
Explaining why x = 0.22 is used as the breakpoint

Most extreme value of fitted 'y' with GAM obtained at 'x' = 0.12
Local range of values considered for breakpoint 'x': [-0.22, 0.49]
t-values for two lines at 'x' = 0.12:
   t1 = 2.92
   t2 = 10.2
We compute t2/(t1+t2) = 0.78
We then lookup the value of 'x' at that quantile, so we run
quantile(x, 0.78) = 0.22 and set that value, 0.22, as the breakpoint.

Note: you may turn off this message by setting `quiet=TRUE`
Robin Hood calculations (see Simonsohn, 2018)
Explaining why x = 0.22 is used as the breakpoint

Most extreme value of fitted 'y' with GAM obtained at 'x' = 0.12
Local range of values considered for breakpoint 'x': [-0.22, 0.49]
t-values for two lines at 'x' = 0.12:
   t1 = 2.92
   t2 = 10.2
We compute t2/(t1+t2) = 0.78
We then lookup the value of 'x' at that quantile, so we run
quantile(x, 0.78) = 0.22 and set that value, 0.22, as the breakpoint.

Note: you may turn off this message by setting `quiet=TRUE`
Robin Hood calculations (see Simonsohn, 2018)
Explaining why x = 0.07 is used as the breakpoint

Most extreme value of fitted 'y' with GAM obtained at 'x' = 0.01
Local range of values considered for breakpoint 'x': [-0.41, 0.38]
t-values for two lines at 'x' = 0.01:
   t1 = 5.51
   t2 = 7.83
We compute t2/(t1+t2) = 0.59
We then lookup the value of 'x' at that quantile, so we run
quantile(x, 0.59) = 0.07 and set that value, 0.07, as the breakpoint.

Note: you may turn off this message by setting `quiet=TRUE`
Robin Hood calculations (see Simonsohn, 2018)
Explaining why x = 0.1 is used as the breakpoint

Most extreme value of fitted 'y' with GAM obtained at 'x' = 0.16
Local range of values considered for breakpoint 'x': [-0.21, 0.42]
t-values for two lines at 'x' = 0.16:
   t1 = 7.8
   t2 = 7.95
We compute t2/(t1+t2) = 0.5
We then lookup the value of 'x' at that quantile, so we run
quantile(x, 0.5) = 0.1 and set that value, 0.1, as the breakpoint.

Note: you may turn off this message by setting `quiet=TRUE`
Robin Hood calculations (see Simonsohn, 2018)
Explaining why x = 0.05 is used as the breakpoint

Most extreme value of fitted 'y' with GAM obtained at 'x' = 0
Local range of values considered for breakpoint 'x': [-0.32, 0.41]
t-values for two lines at 'x' = 0:
   t1 = 8.25
   t2 = 7.01
We compute t2/(t1+t2) = 0.46
We then lookup the value of 'x' at that quantile, so we run
quantile(x, 0.46) = 0.05 and set that value, 0.05, as the breakpoint.

Note: you may turn off this message by setting `quiet=TRUE`
Robin Hood calculations (see Simonsohn, 2018)
Explaining why x = 0.08 is used as the breakpoint

Most extreme value of fitted 'y' with GAM obtained at 'x' = 0.01
Local range of values considered for breakpoint 'x': [-0.17, 0.2]
t-values for two lines at 'x' = 0.01:
   t1 = 8.45
   t2 = 13.54
We compute t2/(t1+t2) = 0.62
We then lookup the value of 'x' at that quantile, so we run
quantile(x, 0.62) = 0.08 and set that value, 0.08, as the breakpoint.

Note: you may turn off this message by setting `quiet=TRUE`
Robin Hood calculations (see Simonsohn, 2018)
Explaining why x = 0.11 is used as the breakpoint

Most extreme value of fitted 'y' with GAM obtained at 'x' = 0.18
Local range of values considered for breakpoint 'x': [0, 0.32]
t-values for two lines at 'x' = 0.18:
   t1 = 11.61
   t2 = 8.11
We compute t2/(t1+t2) = 0.41
We then lookup the value of 'x' at that quantile, so we run
quantile(x, 0.41) = 0.11 and set that value, 0.11, as the breakpoint.

Note: you may turn off this message by setting `quiet=TRUE`
print() and summary() show the same information for lm2()
print() and summary() show the same information for lm2()
print() and summary() show the same information for lm2()
print() and summary() show the same information for lm2()
print() and summary() show the same information for lm2()
Test message
Testmessagewithmultipleparts
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Part1andPart2
Value:42
Count:5items
Test
The p-values are based on quantile regressions that assume all observations are independent
plot_cdf() says: dropped 10 observations with missing 'y' values
plot_cdf() says: dropped 10 observations with missing 'y' values
plot_cdf() says: dropped 10 observations with missing 'y' values
plot_density() says: dropped 10 observations with missing 'y' values
plot_density() says: dropped 10 observations with missing 'y' values
plot_freq() says: dropped 1 observations with missing 'x' values
plot_freq() says: dropped 1 observations with missing 'x' values
         status
         X  Y
group A  2  1
      B  1  1


         status
         X  Y
group A  2  1
      B  1  1


1. Frequencies
      y
     X  Y
x A  2  1
  B  1  1


2. Relative frequencies: by row
              y
         X      Y  Total
x A   .667   .333  1.000
  B   .500   .500  1.000


z = high

      y
     X  Y
x A  1  0
  B  1  0


z = low

      y
     X  Y
x A  0  1
  B  0  1


      y
     X  Y
x A  1  1
  B  1  1

[ FAIL 0 | WARN 0 | SKIP 14 | PASS 601 ]

══ Skipped tests (14) ══════════════════════════════════════════════════════════
• On CRAN (14): 'test-lm2.R:558:1', 'test-lm2.R:567:1', 'test-lm2.R:575:1',
  'test-t.test2.R:336:1', 'test-t.test2.R:347:1', 'test-t.test2.R:359:1',
  'test-t.test2.R:369:1', 'test-t.test2.R:378:1', 'test-t.test2.R:389:1',
  'test-table2.R:307:1', 'test-table2.R:317:1', 'test-table2.R:327:1',
  'test-table2.R:337:1', 'test-table2.R:347:1'

[ FAIL 0 | WARN 0 | SKIP 14 | PASS 601 ]
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> proc.time()
   user  system elapsed 
   9.48    1.06   10.53