testRetestSimData is a simulated dataframe used to demonstrate the testRetestAlpha coefficient function.

This dataset contains the true scores of 250 participants on some variable, and 10 items of a scale administered twice (at t0 and at t1).

Format

A data frame with 250 observations on the following 21 variables.

trueScore: The true scores
t0_item1: Score on item 1 at test
t0_item2: Score on item 2 at test
t0_item3: Score on item 3 at test
t0_item4: Score on item 4 at test
t0_item5: Score on item 5 at test
t0_item6: Score on item 6 at test
t0_item7: Score on item 7 at test
t0_item8: Score on item 8 at test
t0_item9: Score on item 9 at test
t0_item10: Score on item 10 at test
t1_item1: Score on item 1 at retest
t1_item2: Score on item 2 at retest
t1_item3: Score on item 3 at retest
t1_item4: Score on item 4 at retest
t1_item5: Score on item 5 at retest
t1_item6: Score on item 6 at retest
t1_item7: Score on item 7 at retest
t1_item8: Score on item 8 at retest
t1_item9: Score on item 9 at retest
t1_item10: Score on item 10 at retest

Details

This dataset was generated with the code in the reliabilityTest.r test script.

Author

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com

Examples


data(testRetestSimData);
head(testRetestSimData);
#>   trueScore t0_item1 t0_item2 t0_item3 t0_item4 t0_item5 t0_item6  t0_item7
#> 1  18.47356 29.93730 50.23123 30.61498 49.01391 23.01165 32.36001 -16.27159
#> 2  20.25497 39.76955 67.81076 35.74118 44.76242 50.05253 35.03221 -12.50143
#> 3  20.36003 33.48308 42.22236 27.62342 36.27752 39.74102 29.85808 -13.60571
#> 4  17.12198 30.27362 51.64451 25.69399 37.17631 28.56495 22.50433 -15.38949
#> 5  17.44536 31.30345 33.73300 27.53687 30.49654 17.04260 24.90859 -14.29490
#> 6  18.46149 33.09629 56.51762 25.25943 40.53681 32.53490 25.71742 -13.55935
#>   t0_item8 t0_item9 t0_item10 t1_item1 t1_item2 t1_item3 t1_item4 t1_item5
#> 1 18.62356 28.19281  16.55457 34.27009 56.34011 27.30023 41.40305 42.24301
#> 2 20.86903 33.92511  17.18689 30.55629 65.15381 34.34133 36.02030 32.99461
#> 3 17.10305 25.45521  15.52954 34.15362 60.56516 31.28728 43.62388 28.02922
#> 4 10.71415 28.28530  15.84175 31.38832 40.06834 26.58784 31.84802 24.53492
#> 5 15.00101 19.95791  14.03616 34.11844 50.67717 30.42697 30.95247 36.22028
#> 6 15.05864 24.16088  16.28288 36.02580 62.32867 31.57279 47.30800 40.58996
#>   t1_item6  t1_item7 t1_item8 t1_item9 t1_item10
#> 1 35.02187 -13.82493 21.69289 28.89302  15.61633
#> 2 29.91902 -13.55183 14.67212 21.31144  14.85717
#> 3 28.65425 -12.60380 20.07914 28.33966  18.21115
#> 4 24.08168 -14.04168 10.86614 21.73757  13.04613
#> 5 24.66111 -13.62583 19.63161 24.16325  16.11558
#> 6 30.06071 -11.49482 18.76819 28.93773  15.98035
hist(testRetestSimData$t0_item1);

cor(testRetestSimData);
#>           trueScore  t0_item1  t0_item2  t0_item3  t0_item4  t0_item5  t0_item6
#> trueScore 1.0000000 0.5126016 0.5660286 0.5172596 0.5643243 0.4492779 0.5286859
#> t0_item1  0.5126016 1.0000000 0.4646043 0.5060917 0.4910252 0.3884140 0.5457322
#> t0_item2  0.5660286 0.4646043 1.0000000 0.4265309 0.5852347 0.4227765 0.4871109
#> t0_item3  0.5172596 0.5060917 0.4265309 1.0000000 0.4603952 0.4655180 0.4352316
#> t0_item4  0.5643243 0.4910252 0.5852347 0.4603952 1.0000000 0.4480695 0.5644705
#> t0_item5  0.4492779 0.3884140 0.4227765 0.4655180 0.4480695 1.0000000 0.4262135
#> t0_item6  0.5286859 0.5457322 0.4871109 0.4352316 0.5644705 0.4262135 1.0000000
#> t0_item7  0.5069032 0.4339918 0.5037283 0.4338933 0.5353011 0.5121554 0.5072184
#> t0_item8  0.5070424 0.4781048 0.5229818 0.4125417 0.5103903 0.4369460 0.4937599
#> t0_item9  0.5074280 0.4636073 0.4671002 0.3827791 0.4885506 0.4420408 0.4367517
#> t0_item10 0.5807674 0.4999515 0.4782223 0.4576191 0.4952955 0.4637514 0.4794001
#> t1_item1  0.4970000 0.2697570 0.2324916 0.2046261 0.3319180 0.2220899 0.3096957
#> t1_item2  0.5351950 0.1874214 0.2832971 0.2620506 0.2198319 0.1998051 0.2194833
#> t1_item3  0.5257571 0.2510465 0.2995884 0.2345540 0.2674033 0.2740557 0.2794394
#> t1_item4  0.4467991 0.1896167 0.3157308 0.2536295 0.3619082 0.2635696 0.3389556
#> t1_item5  0.4801448 0.1916003 0.2762438 0.2133213 0.2749382 0.2430390 0.2694793
#> t1_item6  0.5603493 0.2718811 0.2608230 0.2136651 0.2555160 0.2343649 0.2931888
#> t1_item7  0.5135826 0.1897554 0.2133114 0.2157206 0.1970393 0.2352373 0.2233035
#> t1_item8  0.4876761 0.1851276 0.2157995 0.2437282 0.2136455 0.1387310 0.2154885
#> t1_item9  0.5296476 0.2349146 0.2854411 0.2236946 0.3316359 0.2374103 0.1912019
#> t1_item10 0.4745415 0.2150442 0.2503530 0.1439450 0.2288002 0.2368534 0.2390417
#>            t0_item7  t0_item8  t0_item9 t0_item10  t1_item1  t1_item2  t1_item3
#> trueScore 0.5069032 0.5070424 0.5074280 0.5807674 0.4970000 0.5351950 0.5257571
#> t0_item1  0.4339918 0.4781048 0.4636073 0.4999515 0.2697570 0.1874214 0.2510465
#> t0_item2  0.5037283 0.5229818 0.4671002 0.4782223 0.2324916 0.2832971 0.2995884
#> t0_item3  0.4338933 0.4125417 0.3827791 0.4576191 0.2046261 0.2620506 0.2345540
#> t0_item4  0.5353011 0.5103903 0.4885506 0.4952955 0.3319180 0.2198319 0.2674033
#> t0_item5  0.5121554 0.4369460 0.4420408 0.4637514 0.2220899 0.1998051 0.2740557
#> t0_item6  0.5072184 0.4937599 0.4367517 0.4794001 0.3096957 0.2194833 0.2794394
#> t0_item7  1.0000000 0.4123229 0.4705156 0.5112051 0.2799645 0.1932820 0.2149115
#> t0_item8  0.4123229 1.0000000 0.4177686 0.5028512 0.2392902 0.2208614 0.3818962
#> t0_item9  0.4705156 0.4177686 1.0000000 0.5089910 0.1764343 0.2016116 0.1396368
#> t0_item10 0.5112051 0.5028512 0.5089910 1.0000000 0.3638106 0.3301314 0.3077104
#> t1_item1  0.2799645 0.2392902 0.1764343 0.3638106 1.0000000 0.3707201 0.4067887
#> t1_item2  0.1932820 0.2208614 0.2016116 0.3301314 0.3707201 1.0000000 0.4585733
#> t1_item3  0.2149115 0.3818962 0.1396368 0.3077104 0.4067887 0.4585733 1.0000000
#> t1_item4  0.3007458 0.2865395 0.2342140 0.3222896 0.3728111 0.4164098 0.4574595
#> t1_item5  0.2819547 0.2991569 0.1607464 0.2850846 0.4212458 0.4828026 0.4651779
#> t1_item6  0.2513542 0.2471390 0.2239523 0.3266980 0.4739204 0.4827881 0.4900555
#> t1_item7  0.1747688 0.2518096 0.2116927 0.2727648 0.3921900 0.4967127 0.4714615
#> t1_item8  0.1325753 0.1679866 0.1108616 0.2840271 0.4390231 0.5656359 0.4814119
#> t1_item9  0.3274092 0.2637880 0.1913770 0.3325094 0.4487356 0.5129317 0.4414149
#> t1_item10 0.1693752 0.1808012 0.1140743 0.2010126 0.3476129 0.4273277 0.4656326
#>            t1_item4  t1_item5  t1_item6  t1_item7  t1_item8  t1_item9 t1_item10
#> trueScore 0.4467991 0.4801448 0.5603493 0.5135826 0.4876761 0.5296476 0.4745415
#> t0_item1  0.1896167 0.1916003 0.2718811 0.1897554 0.1851276 0.2349146 0.2150442
#> t0_item2  0.3157308 0.2762438 0.2608230 0.2133114 0.2157995 0.2854411 0.2503530
#> t0_item3  0.2536295 0.2133213 0.2136651 0.2157206 0.2437282 0.2236946 0.1439450
#> t0_item4  0.3619082 0.2749382 0.2555160 0.1970393 0.2136455 0.3316359 0.2288002
#> t0_item5  0.2635696 0.2430390 0.2343649 0.2352373 0.1387310 0.2374103 0.2368534
#> t0_item6  0.3389556 0.2694793 0.2931888 0.2233035 0.2154885 0.1912019 0.2390417
#> t0_item7  0.3007458 0.2819547 0.2513542 0.1747688 0.1325753 0.3274092 0.1693752
#> t0_item8  0.2865395 0.2991569 0.2471390 0.2518096 0.1679866 0.2637880 0.1808012
#> t0_item9  0.2342140 0.1607464 0.2239523 0.2116927 0.1108616 0.1913770 0.1140743
#> t0_item10 0.3222896 0.2850846 0.3266980 0.2727648 0.2840271 0.3325094 0.2010126
#> t1_item1  0.3728111 0.4212458 0.4739204 0.3921900 0.4390231 0.4487356 0.3476129
#> t1_item2  0.4164098 0.4828026 0.4827881 0.4967127 0.5656359 0.5129317 0.4273277
#> t1_item3  0.4574595 0.4651779 0.4900555 0.4714615 0.4814119 0.4414149 0.4656326
#> t1_item4  1.0000000 0.3940611 0.4661161 0.4554263 0.4348928 0.4209461 0.3341799
#> t1_item5  0.3940611 1.0000000 0.4507101 0.5055954 0.4905989 0.4971334 0.4113071
#> t1_item6  0.4661161 0.4507101 1.0000000 0.4560920 0.5184240 0.4388376 0.4595161
#> t1_item7  0.4554263 0.5055954 0.4560920 1.0000000 0.5153435 0.4570379 0.4325889
#> t1_item8  0.4348928 0.4905989 0.5184240 0.5153435 1.0000000 0.4644051 0.3992053
#> t1_item9  0.4209461 0.4971334 0.4388376 0.4570379 0.4644051 1.0000000 0.4492094
#> t1_item10 0.3341799 0.4113071 0.4595161 0.4325889 0.3992053 0.4492094 1.0000000