tests/testthat/_snaps/statpsych1.md

In statpsych: Statistical Methods for Psychologists

ci.mean returns valid matrix

Code
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Output
   Estimate        SE       LL       UL
       24.5 0.5771157 23.33267 25.66733

ci.stdmean returns valid matrix

Code
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Output
   Estimate adj Estimate        SE        LL       UL
   1.232877     1.209015 0.2124335 0.8165146 1.649239

ci.mean2 returns valid matrix

Code
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Output
                               Estimate        SE        t       df            p
  Equal Variances Assumed:          5.1 0.7151214 7.131656 48.00000 4.621279e-09
  Equal Variances Not Assumed:      5.1 0.6846568 7.448987 46.17476 1.898214e-09
                                     LL       UL
  Equal Variances Assumed:     3.662152 6.537848
  Equal Variances Not Assumed: 3.721998 6.478002

ci.lc.mean.bs returns valid matrix

Code
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Output
                               Estimate       SE         t       df            p
  Equal Variances Assumed:        -5.35 1.300136 -4.114955 36.00000 0.0002152581
  Equal Variances Not Assumed:    -5.35 1.300136 -4.114955 33.52169 0.0002372436
                                      LL        UL
  Equal Variances Assumed:     -7.986797 -2.713203
  Equal Variances Not Assumed: -7.993583 -2.706417

ci.tukey returns valid matrix

Code
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Output
       Estimate       SE          t       df            p         LL         UL
   1 2    -4.71 1.142459  -4.122686 36.20303 5.989090e-04  -7.501842  -1.918158
   1 3   -13.43 1.104078 -12.163998 36.95915 0.000000e+00 -16.125713 -10.734287
   2 3    -8.72 1.228730  -7.096758 37.87646 5.510492e-08 -11.717053  -5.722947

ci.ratio.mean2 returns valid matrix

Code
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Output
   Mean1    Mean2 Mean1/Mean2        LL      UL
    41.5 36.38462    1.140592 0.9837277 1.32247

ci.stdmean2 returns valid matrix

Code
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Output
                           Estimate adj Estimate        SE        LL       UL
  Unweighted standardizer: 1.174493     1.159240 0.2844012 0.6170771 1.731909
  Weighted standardizer:   1.174493     1.159240 0.2802826 0.6251494 1.723837
  Group 1 standardizer:    1.147541     1.117605 0.2975582 0.5643375 1.730744
  Group 2 standardizer:    1.203438     1.172044 0.3120525 0.5918268 1.815050

ci.stdmean.strat returns valid matrix

Code
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Output
                            Estimate adj Estimate         SE         LL        UL
  Weighted standardizer: -0.05538872  -0.05528428 0.10023259 -0.2518410 0.1410636
  Group 1 standardizer:  -0.05714286  -0.05692722 0.10368609 -0.2603639 0.1460782
  Group 2 standardizer:  -0.05357143  -0.05692722 0.09720571 -0.2440911 0.1369483

ci.lc.stdmean.bs returns valid matrix

Code
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Output
                            Estimate adj Estimate        SE        LL         UL
  Unweighted standardizer: -1.301263    -1.273964 0.3692800 -2.025039 -0.5774878
  Weighted standardizer:   -1.301263    -1.273964 0.3514511 -1.990095 -0.6124317
  Group 1 standardizer:    -1.393229    -1.273810 0.4849842 -2.343781 -0.4426775

ci.mean.ps returns valid matrix

Code
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Output
   Estimate       SE        t df           p       LL       UL
        6.8 1.455922 4.670578 29 6.33208e-05 3.822304 9.777696

ci.ratio.mean.ps returns valid matrix

Code
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Output
    Mean1 Mean2 Mean1/Mean2      LL       UL
   3.4875 3.075    1.134146 1.09417 1.175583

ci.stdmean.ps returns valid matrix

Code
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Output
                               Estimate adj Estimate        SE        LL
  Unweighted standardizer:    0.5550319    0.5433457 0.1609934 0.2394905
  Measurement 1 standardizer: 0.5424837    0.5253526 0.1615500 0.2258515
  Measurement 2 standardizer: 0.5684932    0.5505407 0.1692955 0.2366800
                                     UL
  Unweighted standardizer:    0.8705732
  Measurement 1 standardizer: 0.8591158
  Measurement 2 standardizer: 0.9003063

ci.lc.stdmean.ws returns valid matrix

Code
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Output
                            Estimate adj Estimate        SE        LL         UL
  Unweighted standardizer: -1.301263    -1.266557 0.3147937 -1.918248 -0.6842788
  Level 1 standardizer:    -1.393229    -1.337500 0.3661824 -2.110934 -0.6755248

ci.mad returns valid matrix

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Output
   Estimate       SE       LL       UL
       12.5 2.876103 7.962667 19.62282

ci.ratio.mad2 returns valid matrix

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Output
       MAD1     MAD2 MAD1/MAD2        LL       UL
   5.111111 5.888889 0.8679245 0.4520879 1.666253

ci.ratio.mad.ps returns valid matrix

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Output
       MAD1 MAD2 MAD1/MAD2       LL       UL
   12.71429  7.5  1.695238 1.109176 2.590961

ci.cv returns valid matrix

Code
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Output
    Estimate         SE        LL        UL
   0.1489796 0.01817373 0.1214381 0.1926778

ci.ratio.cv2 returns valid matrix

Code
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Output
   Estimate       LL       UL
   1.389188 1.041478 1.854101

ci.cod returns valid matrix

Code
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Output
    Estimate        SE        LL       UL
   0.5921053 0.1814708 0.3813259 1.092679

ci.median returns valid matrix

Code
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Output
   Estimate       SE LL UL
         20 4.270922 10 30

ci.median2 returns valid matrix

Code
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Output
   Median1 Median2 Median1-Median2       SE        LL          UL
      34.5      43            -8.5 4.316291 -16.95977 -0.04022524

ci.ratio.median2 returns valid matrix

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Output
   Median1 Median2 Median1/Median2       LL       UL
        43      37        1.162162 0.927667 1.455933

ci.lc.median.bs returns valid matrix

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Output
   Estimate       SE       LL       UL
      35.77 11.67507 12.88727 58.65273

ci.median.ps returns valid matrix

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Output
   Median1 Median2 Median1-Median2       SE        LL        UL      SE1      SE2
        13      30             -17 3.362289 -23.58996 -10.41004 3.085608 4.509735
        COV
   9.276849

ci.ratio.median.ps returns valid matrix

Code
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Output
   Median1 Median2 Median1/Median2        LL        UL
        13      30       0.4333333 0.3094838 0.6067451

ci.mann returns valid matrix

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Output
   Estimate        SE LL        UL
      0.205 0.1401834  0 0.4797544

ci.random.anova returns valid matrix

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Output
                  Estimate         LL         UL
  Grand mean     59.200000 49.9363896 68.4636104
  Within SD:      9.166782  8.0509046 10.4373219
  Between SD:     8.585948  8.3239359  8.8562078
  Omega-squared:  0.467317  0.2284142  0.8480383

ci.cronbach returns valid matrix

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Output
   Estimate         SE        LL        UL
       0.85 0.02456518 0.7971254 0.8931436

size.ci.mean returns valid number

Code
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Output
   Sample size
            43

size.ci.mean2 returns valid matrix

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Output
   n1 n2
   47 47

size.ci.stdmean2 returns valid matrix

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Output
                              n1  n2
  Unweighted standardizer:   132 132
  Single group standardizer: 141 141

size.ci.ratio.mean2 returns valid matrix

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Output
   n1  n2
   53 106

size.ci.lc.mean.bs returns valid number

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Output
   Sample size per group
                      34

size.ci.stdmean.ps returns valid number

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Output
   Sample size
            19

size.ci.ratio.mean2 returns valid number

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Output
                             Sample size
  Unweighted standardizer:            46
  Single group standardizer:          52

size.ci.ratio.mean.ps returns valid number

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Output
   Sample size
            21

size.ci.lc.stdmean.ws returns valid matrix

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Output
   Sample size
            11

size.ci.lc.mean.ws returns valid matrix

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Output
                             Sample size
  Unweighted standardizer:            26
  Single level standardizer:          35

size.ci.cronbach returns valid number

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Output
   Sample size
            89

size.ci.second returns valid number

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Output
   Second-stage sample size
                         70

size.test.mean returns valid number

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Output
   Sample size
            20

size.test.mean2 returns valid matrix

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Output
   n1 n2
   27 27

size.test.lc.mean.bs returns valid matrix

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Output
   Sample size per group
                      47

size.equiv.mean2 returns valid matrix

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Output
   Sample size per group
                      50

size.supinf.mean2 returns valid matrix

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Output
   Sample size per group
                     143

size.test.mean.ps returns valid number

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Output
   Sample size
            22

size.test.lc.mean.ws returns valid matrix

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Output
   Sample size
            29

size.equiv.mean.ps returns valid number

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Output
   Sample size
            68

size.supinf.mean.ps returns valid number

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Output
   Sample size
            38

size.test.mann returns valid number

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Output
   Sample size per group
                      44

size.test.sign returns valid number

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Output
   Sample size
            67

size.test.sign.ps returns valid number

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Output
   Sample size
            42

size.test.cronbach returns valid number

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Output
   Sample size
           139

pi.score returns valid matrix

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Output
   Predicted df       LL       UL
        24.5 39 17.02546 31.97454

pi.score2 returns valid matrix

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Output
                               Predicted       df       LL       UL
  Equal Variances Assumed:         11.22 83.00000 4.650454 17.78955
  Equal Variances Not Assumed:     11.22 72.34319 4.603642 17.83636

ci.var.upper returns valid number

Code
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Output
         UL
   17.23264

etasqr.adj returns valid number

Code
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Output
   adj Eta-squared
          0.282381

test.anova.bs returns valid matrix

Code
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Output
          F dfA dfE           p Eta-squared adj Eta-squared
   5.919585   2  57 0.004614428   0.1719831       0.1429298

etasqr.gen.2way returns valid matrix

Code
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Output
                                             A         B        AB
  A treatment, B classification:      0.300000 0.5435540 0.1811847
  A classification, B treatment:      0.484252 0.3804878 0.2047244
  A classification, B classification: 0.300000 0.3804878 0.1268293

ci.ratio.cod2 returns valid matrix

Code
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Output
        COD1      COD2 COD1/COD2       LL       UL
   0.1333333 0.1232558  1.081761 0.494964 2.282254

ci.etasqr returns valid matrix

Code
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Output
   Eta-squared adj Eta-squared         SE        LL        UL
         0.241       0.2213707 0.06258283 0.1040229 0.3493431

ci.reliability returns valid vector

Code
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Output
   Estimate        LL        UL
       0.88 0.8489612 0.9065575

ci.sign returns valid matrix

Code
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Output
   Estimate        SE        LL        UL
   0.826087 0.0790342 0.6711828 0.9809911

ci.slope.mean.bs returns valid matrix

Code
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Output
                                Estimate         SE        t       df
  Equal Variances Assumed:     0.3664407 0.06770529 5.412290 36.00000
  Equal Variances Not Assumed: 0.3664407 0.07336289 4.994905 18.65826
                                          p        LL        UL
  Equal Variances Assumed:     4.242080e-06 0.2291280 0.5037534
  Equal Variances Not Assumed: 8.468223e-05 0.2126998 0.5201815

test.mono.mean.bs returns valid matrix

Code
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Output
       Estimate       SE        LL         UL
   1 2   -11.71 4.139530 -22.07803 -1.3419744
   2 3   -11.72 4.399497 -22.74731 -0.6926939
   3 4   -16.92 4.730817 -28.76921 -5.0707936

power.mean returns valid matrix

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Output
       Power
   0.8021669

power.mean2 returns valid matrix

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Output
       Power
   0.8398417

power.mean.ps returns valid matrix

Code
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Output
       Power
   0.9074354

power.lc.bs returns valid matrix

Code
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Output
       Power
   0.7221171

ci.cqv returns valid matrix

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Output
   Estimate        SE        LL        UL
        0.5 0.1552485 0.2617885 0.8841821

ci.ratio.sd2 returns valid matrix

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Output
        SD1      SD2   SD1/SD2       LL       UL
   5.711587 6.450667 0.8854257 0.486279 1.728396

size.ci.etasqr returns valid matrix

Code
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Output
   Sample size per group
                      63

ci.2x2.stdmean.bs returns valid matrix

Code
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Output
              Estimate adj Estimate        SE         LL         UL
  AB:      -1.44976487   -1.4193502 0.6885238 -2.7992468 -0.1002829
  A:        0.46904158    0.4592015 0.3379520 -0.1933321  1.1314153
  B:       -0.75330920   -0.7375055 0.3451209 -1.4297338 -0.0768846
  A at b1: -0.25584086   -0.2504736 0.4640186 -1.1653006  0.6536189
  A at b2:  1.19392401    1.1688767 0.5001423  0.2136630  2.1741850
  B at a1: -1.47819163   -1.4471806 0.4928386 -2.4441376 -0.5122457
  B at a2: -0.02842676   -0.0278304 0.4820369 -0.9732017  0.9163482

ci.2x2.median.bs returns valid matrix

Code
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Output
           Estimate       SE         LL         UL
  AB:          -5.0 3.389735 -11.643758 1.64375833
  A:            1.5 1.694867  -1.821879 4.82187916
  B:           -2.0 1.694867  -5.321879 1.32187916
  A at b1:     -1.0 2.152661  -5.219138 3.21913797
  A at b2:      4.0 2.618464  -1.132095 9.13209504
  B at a1:     -4.5 2.311542  -9.030539 0.03053939
  B at a2:      0.5 2.479330  -4.359397 5.35939682

ci.2x2.stdmean.ws returns valid matrix

Code
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Output
              Estimate adj Estimate         SE           LL        UL
  AB:       0.17248839   0.16446123 0.13654635 -0.095137544 0.4401143
  A:        0.10924265   0.10415878 0.05752822 -0.003510596 0.2219959
  B:        0.07474497   0.07126653 0.05920554 -0.041295751 0.1907857
  A at b1:  0.19548684   0.18638939 0.08460680  0.029660560 0.3613131
  A at b2:  0.02299845   0.02192816 0.09371838 -0.160686202 0.2066831
  B at a1:  0.16098916   0.15349715 0.09457347 -0.024371434 0.3463498
  B at a2: -0.01149923  -0.01096408 0.08595873 -0.179975237 0.1569768

ci.2x2.stdmean.mixed returns valid matrix

Code
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Output
              Estimate adj Estimate        SE         LL         UL
  AB:      -1.95153666  -1.80141845 1.0268728 -3.9641704 0.06109706
  A:        1.90911195   1.82026682 0.5190413  0.8918096 2.92641425
  B:        1.06061775   0.97903177 0.3711681  0.3331416 1.78809392
  A at b1:  0.93334362   0.83480791 0.6028071 -0.2481367 2.11482389
  A at b2:  2.88488027   2.58031536 0.8396553  1.2391862 4.53057438
  B at a1:  0.08484942   0.07832254 0.5469232 -0.9871003 1.15679910
  B at a2:  2.03638608   1.87974099 0.7113341  0.6421968 3.43057538

ci.2x2.median.mixed returns valid matrix

Code
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Output
           Estimate       SE         LL        UL
  AB:         -3.50 2.681476 -8.7555973  1.755597
  A:           1.75 1.340738 -0.8777986  4.377799
  B:           4.25 1.028850  2.2334918  6.266508
  A at b1:     2.50 1.680868 -0.7944405  5.794441
  A at b2:     6.00 2.089258  1.9051295 10.094870
  B at a1:     0.00 1.313181 -2.5737873  2.573787
  B at a2:     3.50 1.996942 -0.4139342  7.413934

ci.2x2.median.w returns valid matrix

Code
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Output
           Estimate        SE         LL       UL
  AB:          2.50 21.050122 -38.757482 43.75748
  A:          24.75  9.603490   5.927505 43.57250
  B:          18.25  9.101881   0.410641 36.08936
  A at b1:    26.00 11.813742   2.845491 49.15451
  A at b2:    23.50 16.323093  -8.492675 55.49267
  B at a1:    19.50 15.710347 -11.291715 50.29171
  B at a2:    17.00 11.850202  -6.225970 40.22597

pi.var example

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Output
        UL
   23.9724

pi.var.upper returns valid matrix

Code
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Output
         UL
   19.08182

ci.bayes.normal returns valid matrix

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Output
   Posterior mean Posterior SD       LL       UL
          24.9226    0.5543895 23.83602 26.00919

spearmanbrown returns valid matrix

Code
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Output
   Reliability of r2 measurements
                             0.75

ci.mean.fpc returns valid matrix

Code
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Output
   Estimate        SE       LL       UL
       24.5 0.5381631 23.41146 25.58854

test.mean returns valid number

Code
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Output
          t df          p
   2.599132 39 0.01312665

size.ci.mean.prior returns valid matrix

Code
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Output
   Sample size
            44

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