tests/testthat/_snaps/statpsych2.md

In statpsych: Statistical Methods for Psychologists

ci.cor returns valid matrix

Code
  res
Output
   Estimate        SE        LL        UL
      0.536 0.1018149 0.2978573 0.7058914

ci.spcor returns valid matrix

Code
  res
Output
   Estimate        SE        LL        UL
      0.582 0.1374298 0.2525662 0.7905182

ci.cor2 returns valid matrix

Code
  res
Output
   Estimate         SE         LL        UL
      0.084 0.02967934 0.02803246 0.1463609

ci.cor.dep returns valid matrix

Code
  res
Output
   Estimate        SE         LL       UL
      0.217 0.1026986 0.01323072 0.415802

ci.cor2.gen returns valid matrix

Code
  res
Output
   Estimate   LL        UL
        0.2 0.07 0.3220656

ci.pbcor returns valid matrix

Code
  res
Output
               Estimate         SE        LL        UL
  Weighted:   0.7065799 0.04890959 0.5885458 0.7854471
  Unweighted: 0.7020871 0.05018596 0.5808366 0.7828948

ci.spear returns valid matrix

Code
  res
Output
    Estimate         SE        LL        UL
   0.8699639 0.08241326 0.5840951 0.9638297

ci.spear2 returns valid matrix

Code
  res
Output
   Estimate         SE         LL        UL
       0.06 0.08124926 -0.1003977 0.2185085

ci.mape returns valid matrix

Code
  res
Output
   Estimate        SE       LL       UL
     2.3744 0.3314752 1.806022 3.121654

ci.condslope returns valid matrix

Code
  res
Output
                    Estimate        SE        t  df           p        LL
  At low moderator    0.9328 0.4109570 2.269824 122 0.024973618 0.1192696
  At high moderator   1.7644 0.6070517 2.906507 122 0.004342076 0.5626805
                          UL
  At low moderator  1.746330
  At high moderator 2.966119

ci.lc.reg returns valid matrix

Code
  res
Output
   Estimate        SE        t      df          p        LL       UL
      1.303 0.5085838 2.562016 78.8197 0.01231256 0.2906532 2.315347

ci.fisher returns valid matrix

Code
  res
Output
       Estimate        LL        UL
  [1,]    0.641 0.5276396 0.7319293

size.ci.slope returns valid numeric

Code
  res
Output
   Total sample size
                  83

size.ci.cor returns valid numeric

Code
  res
Output
   Sample size
           188

size.ci.spear returns valid numeric

Code
  res
Output
   Sample size
           200

size.ci.pbcor returns valid numeric

Code
  res
Output
   Sample size
           168

Code
  res
Output
   Sample size
           168

size.ci.rsqr returns valid numeric

Code
  res
Output
   Sample size
           226

size.ci.condmean returns valid numeric

Code
  res
Output
   Total sample size
                 210

size.ci.lc.ancova returns valid numeric

Code
  res
Output
   Sample size per group
                      21

size.test.slope returns valid numeric

Code
  res
Output
   Total sample size
                 100

size.test.cor returns valid numeric

Code
  res
Output
   Sample size
            48

size.interval.cor returns valid numeric

Code
  res
Output
   Sample size
           360

size.test.lc.ancova returns valid numeric

Code
  res
Output
   Sample size per group
                      46

ci.rsqr returns valid matrix

Code
  res
Output
   R-squared adj R-squared         SE         LL        UL
       0.241     0.2206696 0.06752263 0.09819599 0.3628798

ci.lc.gen.bs returns valid matrix

Code
  res
Output
   Estimate        SE       LL       UL
       1.63 0.2573806 1.125543 2.134457

ci.lc.glm returns valid matrix

Code
  res
Output
   Estimate        SE       t df           p       LL       UL
   2.931111 0.4462518 6.56829  7 0.000313428 1.875893 3.986329

ci.theil returns valid matrix

Code
  res
Output
   Estimate        SE        LL   UL
        0.5 0.1085927 0.3243243 0.75

power.cor returns valid matrix

Code
  res
Output
       Power
   0.7751947

power.cor2 returns valid matrix

Code
  res
Output
       Power
   0.5919682

size.test.cor2 returns valid matrix

Code
  res
Output
    n1  n2
   245 490

size.test.cronbach2 returns valid matrix

Code
  res
Output
   Sample size per group
                      77

size.ci.cronbach2 returns valid matrix

Code
  res
Output
   Sample size per group
                     180

size.ci.mape returns valid numeric

Code
  res
Output
   Sample size
            57

size.ci.indirect returns valid matrix

Code
  res
Output
   Sample size
           106

ci.ratio.mape2 returns valid matrix

Code
  res
Output
     MAPE1     MAPE2 MAPE1/MAPE2       LL       UL
   2.58087 0.8327273    3.099298 1.917003 5.010761

ci.rel2 returns valid matrix

Code
  res
Output
   Estimate   LL        UL
        0.2 0.07 0.3220656

ci.cronbach2 returns valid matrix

Code
  res
Output
   Estimate         LL       UL
       0.12 0.06973411 0.173236

ci.bscor returns valid matrix

Code
  res
Output
    Estimate         SE        LL       UL
   0.8855666 0.06129908 0.7376327 0.984412

pi.cor returns valid matrix

Code
  res
Output
          LL        UL
   0.6034092 0.8573224

test.cor returns valid matrix

Code
  res
Output
   Estimate        z           p
      0.484 3.205432 0.001348601

test.spear returns valid matrix

Code
  res
Output
   Estimate        z          p
      0.471 3.009628 0.00261568

test.cor2 returns valid matrix

Code
  res
Output
   Estimate        z           p
      0.247 2.705709 0.006815877

test.spear2 returns valid matrix

Code
  res
Output
   Estimate        z          p
      0.247 2.498645 0.01246691

size.ci.cor2 returns valid matrix

Code
  res
Output
   Sample size per group
                     271

size.ci.spear2 returns valid matrix

Code
  res
Output
   Sample size per group
                     314

size.ci.cor.prior returns valid matrix

Code
  res
Output
   Sample size
           331

adj.se returns valid matrix

Code
  res
Output
       Estimate   adj SE        t  df           p        LL        UL
  [1,]     3.78 1.738243 2.174609 114 0.031725582 0.3365531  7.223447
  [2,]     8.21 3.487559 2.354082 114 0.020279958 1.3011734 15.118827
  [3,]     2.99 1.087233 2.750102 114 0.006930554 0.8362007  5.143799

fitindices returns valid matrix

Code
  res
Output
         NFI   adj NFI       CFI       TLI      RMSEA
   0.9450141 0.9837093 0.9823428 0.9646857 0.03746109

size.ci.biphi example

Code
  res
Output
   Sample size
           195

size.ci.ancova2 example

Code
  res
Output
   n1 n2
   16 32

size.ci.slope.gen example

Code
  res
Output
   Sample size
           305

size.test.ancova2 example

Code
  res
Output
   n1 n2
   47 94

size.test.slope.gen example

Code
  res
Output
   Sample size
           156

signal example

Code
  res
Output
          HR      FAR  d-prime  Threshold       Bias
   0.8168317 0.460396 1.002793 0.09943603 -0.4019603

expon.slope example

Code
  res
Output
                    Estimate        LL       UL
  exp(B)            1.652022  1.528651  1.78535
  100[exp(B) - 1]% 65.202201 52.865066 78.53502

ci.bayes.cor example

Code
  res
Output
   Posterior mean         LL        UL
        0.1873765 0.02795441 0.3375031

ci.bayes.spcor example

Code
  res
Output
   Posterior mean         LL        UL
        0.2272797 0.07288039 0.3710398

statpsych documentation built on April 4, 2025, 3:20 a.m.