tests/testthat/_snaps/estimate_mdiff_two.md
In rcalinjageman/esci: Estimation Statistics with Confidence Intervals
Compare estimate_mdiff_two to ESCI_Data_two, penlaptop1
Code
estimate
Output
Analysis of raw data:
Outcome variable(s) = % Transcription
Grouping variable(s) = Note-taking type
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 % Transcription Note-taking type Ref-Laptop 6.88
2 % Transcription Note-taking type Comp-Pen 12.09
mean_LL mean_UL sd n df mean_SE
1 5.412432 8.347568 4.22 48 149 0.7426914
2 11.088156 13.091844 5.52 103 149 0.5070029
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison % Transcription Note-taking type Comp-Pen
2 Reference % Transcription Note-taking type Ref-Laptop
3 Difference % Transcription Note-taking type Comp-Pen ‒ Ref-Laptop
effect_size LL UL SE df ta_LL ta_UL
1 12.09 11.088156 13.091844 0.5070029 149 11.250837 12.929163
2 6.88 5.412432 8.347568 0.7426914 149 5.650738 8.109262
3 5.21 3.433079 6.986921 0.8992455 149 3.721619 6.698381
-- es_smd --
outcome_variable_name grouping_variable_name effect
1 % Transcription Note-taking type Comp-Pen ‒ Ref-Laptop
effect_size LL UL numerator denominator SE df d_biased
1 1.007425 0.6448059 1.366989 5.21 5.145517 0.1842337 149 1.012532
This standardized mean difference is called d_s because the standardizer used was s_p. d_s has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
Note: LL and UL are lower and upper boundaries of confidence intervals with 95% expected coverage.
Code
estimate_99
Output
Analysis of raw data:
Outcome variable(s) = % Transcription
Grouping variable(s) = Note-taking type
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 % Transcription Note-taking type Laptop 6.88
2 % Transcription Note-taking type Pen 12.09
mean_LL mean_UL sd n df mean_SE
1 4.942149 8.817851 4.22 48 149 0.7426914
2 10.767114 13.412886 5.52 103 149 0.5070029
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison % Transcription Note-taking type Pen
2 Reference % Transcription Note-taking type Laptop
3 Difference % Transcription Note-taking type Pen ‒ Laptop
effect_size LL UL SE df ta_LL ta_UL
1 12.09 10.767114 13.412886 0.5070029 149 10.897714 13.282286
2 6.88 4.942149 8.817851 0.7426914 149 5.133461 8.626539
3 5.21 2.863664 7.556336 0.8992455 149 3.095303 7.324697
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 % Transcription Note-taking type Pen ‒ Laptop 1.007425
LL UL numerator denominator SE df d_biased
1 0.5315012 1.48061 5.21 5.145517 0.1842337 149 1.012532
This standardized mean difference is called d_s because the standardizer used was s_p. d_s has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Code
mytest
Output
$properties
$properties$effect_size_name
[1] "mean"
$properties$alpha
[1] 0.05
$properties$interval_null
[1] FALSE
$properties$rope
[1] 0 0
$properties$rope_units
[1] "raw"
$point_null
test_type outcome_variable_name effect null_words
1 Nil Hypothesis Test % Transcription Comp-Pen ‒ Ref-Laptop 0.00
confidence LL UL CI
1 95 3.433079 6.986921 95% CI [3.433079, 6.986921]
CI_compare t df p p_result
1 The 95% CI does not contain H_0 5.793746 149 3.951374e-08 p < 0.05
null_decision conclusion
1 Reject H_0 At α = 0.05, 0.00 is not a plausible value of μ_diff
significant
1 TRUE
Code
estimate
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = transcription
Grouping variable(s) = condition
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level
1 transcription condition Pen
2 transcription condition Laptop
mean mean_LL mean_UL median median_LL median_UL sd min max
1 8.811765 6.724559 10.89897 8.6 6.598482 10.60152 4.749339 1.0 20.1
2 14.519355 12.333487 16.70522 12.8 9.469511 16.13049 7.285576 1.2 34.7
q1 q3 n missing df mean_SE median_SE
1 5.20 11.275 34 0 63 1.044470 1.021201
2 9.45 17.850 31 0 63 1.093842 1.699260
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison transcription condition Laptop
2 Reference transcription condition Pen
3 Difference transcription condition Laptop ‒ Pen
effect_size LL UL SE df ta_LL ta_UL
1 14.519355 12.333487 16.705223 1.093842 63 12.693293 16.345416
2 8.811765 6.724559 10.898971 1.044470 63 7.068125 10.555405
3 5.707590 2.685265 8.729915 1.512417 63 3.182757 8.232423
-- es_median_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison transcription condition Laptop
2 Reference transcription condition Pen
3 Difference transcription condition Laptop ‒ Pen
effect_size LL UL SE ta_LL ta_UL
1 12.8 9.4695114 16.130489 1.699260 10.004966 15.595034
2 8.6 6.5984823 10.601518 1.021201 6.920273 10.279727
3 4.2 0.3143563 8.085644 1.982508 0.939065 7.460935
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 transcription condition Laptop ‒ Pen 0.9259595
LL UL numerator denominator SE df d_biased
1 0.4098655 1.435414 5.70759 6.090252 0.2616245 63 0.9371681
This standardized mean difference is called d_s because the standardizer used was s_p. d_s has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
-- es_mean_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 transcription condition Laptop / Pen 1.647724
LL UL comparison_mean reference_mean
1 1.273045 2.132677 14.51935 8.811765
[1] "This effect-size measure is appropriate only for true ratio scales."
-- es_median_ratio --
outcome_variable_name grouping_variable_name effect effect_size LL
1 transcription condition Laptop / Pen 1.488372 1.06252
UL comparison_median reference_median
1 2.084903 12.8 8.6
[1] "This effect-size measure is appropriate only for true ratio scales."
Note: LL and UL are lower and upper boundaries of confidence intervals with 95% expected coverage.
Code
mytest
Output
$properties
$properties$effect_size_name
[1] "mean"
$properties$alpha
[1] 0.05
$properties$interval_null
[1] FALSE
$properties$rope
[1] 0 0
$properties$rope_units
[1] "raw"
$point_null
test_type outcome_variable_name effect null_words confidence
1 Nil Hypothesis Test transcription Laptop ‒ Pen 0.00 95
LL UL CI CI_compare
1 2.685265 8.729915 95% CI [2.685265, 8.729915] The 95% CI does not contain H_0
t df p p_result null_decision
1 3.77382 63 0.0003579282 p < 0.05 Reject H_0
conclusion significant
1 At α = 0.05, 0.00 is not a plausible value of μ_diff TRUE
Code
estimate_99
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = transcription
Grouping variable(s) = condition
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level
1 transcription condition Pen
2 transcription condition Laptop
mean mean_LL mean_UL median median_LL median_UL sd min max
1 8.811765 6.037502 11.58603 8.6 5.969560 11.23044 4.749339 1.0 20.1
2 14.519355 11.613953 17.42476 12.8 8.422996 17.17700 7.285576 1.2 34.7
q1 q3 n missing df mean_SE median_SE
1 5.20 11.275 34 0 63 1.044470 1.021201
2 9.45 17.850 31 0 63 1.093842 1.699260
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison transcription condition Laptop
2 Reference transcription condition Pen
3 Difference transcription condition Laptop ‒ Pen
effect_size LL UL SE df ta_LL ta_UL
1 14.519355 11.613953 17.42476 1.093842 63 11.908346 17.130363
2 8.811765 6.037502 11.58603 1.044470 63 6.318608 11.304922
3 5.707590 1.690390 9.72479 1.512417 63 2.097438 9.317742
-- es_median_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison transcription condition Laptop
2 Reference transcription condition Pen
3 Difference transcription condition Laptop ‒ Pen
effect_size LL UL SE ta_LL ta_UL
1 12.8 8.4229960 17.177004 1.699260 8.8469299 16.753070
2 8.6 5.9695599 11.230440 1.021201 6.2243306 10.975669
3 4.2 -0.9066015 9.306602 1.982508 -0.4120026 8.812003
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 transcription condition Laptop ‒ Pen 0.9259595
LL UL numerator denominator SE df d_biased
1 0.2490821 1.59688 5.70759 6.090252 0.2616245 63 0.9371681
This standardized mean difference is called d_s because the standardizer used was s_p. d_s has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
-- es_mean_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 transcription condition Laptop / Pen 1.647724
LL UL comparison_mean reference_mean
1 1.169397 2.321705 14.51935 8.811765
[1] "This effect-size measure is appropriate only for true ratio scales."
-- es_median_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 transcription condition Laptop / Pen 1.488372
LL UL comparison_median reference_median
1 0.9557473 2.317821 12.8 8.6
[1] "This effect-size measure is appropriate only for true ratio scales."
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Compare estimate_mdiff_two to statpsych::ci.mean2 example
Code
estimate
Output
Analysis of raw data:
Outcome variable(s) = My outcome variable
Grouping variable(s) = My grouping variable
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 My outcome variable My grouping variable Control 10.3
2 My outcome variable My grouping variable Treated 15.4
mean_LL mean_UL sd n df mean_SE
1 8.924592 11.67541 2.15 20 19 0.4807546
2 14.056336 16.74366 2.67 30 29 0.4874731
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison My outcome variable My grouping variable Treated
2 Reference My outcome variable My grouping variable Control
3 Difference My outcome variable My grouping variable Treated ‒ Control
effect_size LL UL SE df ta_LL ta_UL
1 15.4 14.056336 16.743664 0.4874731 29.00000 14.199831 16.600169
2 10.3 8.924592 11.675408 0.4807546 19.00000 9.079132 11.520868
3 5.1 3.260617 6.939383 0.6846568 46.17476 3.450073 6.749927
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 My outcome variable My grouping variable Treated ‒ Control 2.070897
LL UL numerator denominator SE df d_biased
1 1.187684 3.013583 5.1 2.423984 0.5604936 47.99877 2.103974
This standardized mean difference is called d_avg because the standardizer used was s_avg. d_avg has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Compare estimate_mdiff_two to statpsych::ci.median2 example
Code
estimate
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = myoutcome
Grouping variable(s) = mycondition
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 myoutcome mycondition Group 1 34.2
2 myoutcome mycondition Group 2 41.5
mean_LL mean_UL median median_LL median_UL sd min max q1 q3 n
1 28.33027 40.06973 34.5 27.21846 41.78154 5.711587 26 43 29.75 38.50 10
2 34.87072 48.12928 43.0 34.59823 51.40177 6.450667 31 49 36.75 46.75 10
missing df mean_SE median_SE
1 0 9 1.806162 2.826871
2 0 9 2.039880 3.261774
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE df ta_LL ta_UL
1 34.2 28.33027 40.0697304 1.806162 9.00000 29.10403 39.2959748
2 41.5 34.87072 48.1292751 2.039880 9.00000 35.74460 47.2553953
3 -7.3 -15.15592 0.5559194 2.724579 17.73989 -14.26401 -0.3359923
-- es_median_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE ta_LL ta_UL
1 34.5 27.21846 41.781536 2.826871 27.92372 41.076285
2 43.0 34.59823 51.401773 3.261774 35.41198 50.588021
3 -8.5 -19.61803 2.618029 4.316291 -18.54119 1.541194
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 ‒ Group 2 -1.146719
LL UL numerator denominator SE df d_biased
1 -2.448433 0.07467368 -7.3 6.092345 0.6550008 17.73989 -1.198225
This standardized mean difference is called d_avg because the standardizer used was s_avg. d_avg has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
-- es_mean_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 / Group 2 0.8240964
LL UL comparison_mean reference_mean
1 0.6694745 1.01443 34.2 41.5
[1] "This effect-size measure is appropriate only for true ratio scales."
-- es_median_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 / Group 2 0.8023256
LL UL comparison_median reference_median
1 0.5919106 1.08754 34.5 43
[1] "This effect-size measure is appropriate only for true ratio scales."
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Compare estimate_mdiff_two to statpsych::ci.ratio.mean2 and ci.ratio.median2 example
Code
estimate
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = myoutcome
Grouping variable(s) = mycondition
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 myoutcome mycondition Group 1 41.50000
2 myoutcome mycondition Group 2 36.38462
mean_LL mean_UL median median_LL median_UL sd min max q1 q3 n
1 34.87072 48.12928 43 34.59823 51.40177 6.450667 31 49 36.75 46.75 10
2 30.67493 42.09430 37 29.66461 44.33539 6.739664 26 49 32.00 40.00 13
missing df mean_SE median_SE
1 0 9 2.039880 3.261774
2 0 12 1.869247 2.847778
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE df ta_LL ta_UL
1 41.500000 34.870725 48.12928 2.039880 9.00000 35.744605 47.25540
2 36.384615 30.674928 42.09430 1.869247 12.00000 31.373169 41.39606
3 5.115385 -2.760215 12.99098 2.766802 19.92414 -1.881322 12.11209
-- es_median_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE ta_LL ta_UL
1 43 34.598227 51.40177 3.261774 35.411979 50.58802
2 37 29.664610 44.33539 2.847778 30.375078 43.62492
3 6 -5.153373 17.15337 4.330013 -4.073115 16.07312
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 ‒ Group 2 0.7470702
LL UL numerator denominator SE df d_biased
1 -0.3558306 1.890873 5.115385 6.596749 0.517002 20.79173 0.7754403
This standardized mean difference is called d_avg because the standardizer used was s_avg. d_avg has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
-- es_mean_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 / Group 2 1.140592
LL UL comparison_mean reference_mean
1 0.9324275 1.395229 41.5 36.38462
[1] "This effect-size measure is appropriate only for true ratio scales."
-- es_median_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 / Group 2 1.162162
LL UL comparison_median reference_median
1 0.8642465 1.562773 43 37
[1] "This effect-size measure is appropriate only for true ratio scales."
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Code
estimate
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = myoutcome
Grouping variable(s) = mycondition
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 myoutcome mycondition Group 1 23.70000
2 myoutcome mycondition Group 2 25.46154
mean_LL mean_UL median median_LL median_UL sd min max q1 q3 n
1 -2.399473 49.79947 37.5 -0.8577566 75.85776 36.48455 -47 49 31.5 45.5 10
2 8.614096 42.30898 35.0 28.1304096 41.86959 27.87955 -39 49 27.0 40.0 13
missing df mean_SE median_SE
1 0 9 11.537427 19.570644
2 0 12 7.732396 3.504957
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE df ta_LL ta_UL
1 23.700000 -2.399473 49.79947 11.537427 9.00000 2.550593 44.84941
2 25.461538 8.614096 42.30898 7.732396 12.00000 11.680186 39.24289
3 -1.761538 -31.144112 27.62103 13.888922 16.41673 -25.972286 22.44921
-- es_median_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE ta_LL ta_UL
1 37.5 -0.8577566 75.85776 19.570644 5.309156 69.69084
2 35.0 28.1304096 41.86959 3.504957 29.234858 40.76514
3 2.5 -36.4680480 41.46805 19.882022 -30.203017 35.20302
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 ‒ Group 2 -0.05195366
LL UL numerator denominator SE df d_biased
1 -0.8920995 0.7850884 -1.761538 32.46838 0.4541995 17.98107 -0.05425397
This standardized mean difference is called d_avg because the standardizer used was s_avg. d_avg has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
-- es_mean_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 / Group 2 0.9308157
LL UL comparison_mean reference_mean
1 0.275107 3.149385 23.7 25.46154
[1] "WARNING! Your dataset includes negative values. This effect-size measure is appropriate only for true ratio scales."
-- es_median_ratio --
outcome_variable_name grouping_variable_name effect effect_size LL
1 myoutcome mycondition Group 1 / Group 2 NA NA
UL comparison_median reference_median
1 NA NA NA
[1] "WARNING! Your dataset includes negative values. This effect-size measure is appropriate only for true ratio scales."
Note: LL and UL are lower and upper boundaries of confidence intervals with 95% expected coverage.
Warnings:
* The ratio between group effect size is appropriate only for true ratio scales where values < 0 are impossible. Your data include at least one negative value, so the requested ratio effect size is not reported.
rcalinjageman/esci documentation built on Dec. 23, 2024, 2:37 p.m.
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Compare estimate_mdiff_two to ESCI_Data_two, penlaptop1
Code
estimate
Output
Analysis of raw data:
Outcome variable(s) = % Transcription
Grouping variable(s) = Note-taking type
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 % Transcription Note-taking type Ref-Laptop 6.88
2 % Transcription Note-taking type Comp-Pen 12.09
mean_LL mean_UL sd n df mean_SE
1 5.412432 8.347568 4.22 48 149 0.7426914
2 11.088156 13.091844 5.52 103 149 0.5070029
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison % Transcription Note-taking type Comp-Pen
2 Reference % Transcription Note-taking type Ref-Laptop
3 Difference % Transcription Note-taking type Comp-Pen ‒ Ref-Laptop
effect_size LL UL SE df ta_LL ta_UL
1 12.09 11.088156 13.091844 0.5070029 149 11.250837 12.929163
2 6.88 5.412432 8.347568 0.7426914 149 5.650738 8.109262
3 5.21 3.433079 6.986921 0.8992455 149 3.721619 6.698381
-- es_smd --
outcome_variable_name grouping_variable_name effect
1 % Transcription Note-taking type Comp-Pen ‒ Ref-Laptop
effect_size LL UL numerator denominator SE df d_biased
1 1.007425 0.6448059 1.366989 5.21 5.145517 0.1842337 149 1.012532
This standardized mean difference is called d_s because the standardizer used was s_p. d_s has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
Note: LL and UL are lower and upper boundaries of confidence intervals with 95% expected coverage.
Code
estimate_99
Output
Analysis of raw data:
Outcome variable(s) = % Transcription
Grouping variable(s) = Note-taking type
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 % Transcription Note-taking type Laptop 6.88
2 % Transcription Note-taking type Pen 12.09
mean_LL mean_UL sd n df mean_SE
1 4.942149 8.817851 4.22 48 149 0.7426914
2 10.767114 13.412886 5.52 103 149 0.5070029
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison % Transcription Note-taking type Pen
2 Reference % Transcription Note-taking type Laptop
3 Difference % Transcription Note-taking type Pen ‒ Laptop
effect_size LL UL SE df ta_LL ta_UL
1 12.09 10.767114 13.412886 0.5070029 149 10.897714 13.282286
2 6.88 4.942149 8.817851 0.7426914 149 5.133461 8.626539
3 5.21 2.863664 7.556336 0.8992455 149 3.095303 7.324697
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 % Transcription Note-taking type Pen ‒ Laptop 1.007425
LL UL numerator denominator SE df d_biased
1 0.5315012 1.48061 5.21 5.145517 0.1842337 149 1.012532
This standardized mean difference is called d_s because the standardizer used was s_p. d_s has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Code
mytest
Output
$properties
$properties$effect_size_name
[1] "mean"
$properties$alpha
[1] 0.05
$properties$interval_null
[1] FALSE
$properties$rope
[1] 0 0
$properties$rope_units
[1] "raw"
$point_null
test_type outcome_variable_name effect null_words
1 Nil Hypothesis Test % Transcription Comp-Pen ‒ Ref-Laptop 0.00
confidence LL UL CI
1 95 3.433079 6.986921 95% CI [3.433079, 6.986921]
CI_compare t df p p_result
1 The 95% CI does not contain H_0 5.793746 149 3.951374e-08 p < 0.05
null_decision conclusion
1 Reject H_0 At α = 0.05, 0.00 is not a plausible value of μ_diff
significant
1 TRUE
Code
estimate
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = transcription
Grouping variable(s) = condition
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level
1 transcription condition Pen
2 transcription condition Laptop
mean mean_LL mean_UL median median_LL median_UL sd min max
1 8.811765 6.724559 10.89897 8.6 6.598482 10.60152 4.749339 1.0 20.1
2 14.519355 12.333487 16.70522 12.8 9.469511 16.13049 7.285576 1.2 34.7
q1 q3 n missing df mean_SE median_SE
1 5.20 11.275 34 0 63 1.044470 1.021201
2 9.45 17.850 31 0 63 1.093842 1.699260
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison transcription condition Laptop
2 Reference transcription condition Pen
3 Difference transcription condition Laptop ‒ Pen
effect_size LL UL SE df ta_LL ta_UL
1 14.519355 12.333487 16.705223 1.093842 63 12.693293 16.345416
2 8.811765 6.724559 10.898971 1.044470 63 7.068125 10.555405
3 5.707590 2.685265 8.729915 1.512417 63 3.182757 8.232423
-- es_median_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison transcription condition Laptop
2 Reference transcription condition Pen
3 Difference transcription condition Laptop ‒ Pen
effect_size LL UL SE ta_LL ta_UL
1 12.8 9.4695114 16.130489 1.699260 10.004966 15.595034
2 8.6 6.5984823 10.601518 1.021201 6.920273 10.279727
3 4.2 0.3143563 8.085644 1.982508 0.939065 7.460935
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 transcription condition Laptop ‒ Pen 0.9259595
LL UL numerator denominator SE df d_biased
1 0.4098655 1.435414 5.70759 6.090252 0.2616245 63 0.9371681
This standardized mean difference is called d_s because the standardizer used was s_p. d_s has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
-- es_mean_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 transcription condition Laptop / Pen 1.647724
LL UL comparison_mean reference_mean
1 1.273045 2.132677 14.51935 8.811765
[1] "This effect-size measure is appropriate only for true ratio scales."
-- es_median_ratio --
outcome_variable_name grouping_variable_name effect effect_size LL
1 transcription condition Laptop / Pen 1.488372 1.06252
UL comparison_median reference_median
1 2.084903 12.8 8.6
[1] "This effect-size measure is appropriate only for true ratio scales."
Note: LL and UL are lower and upper boundaries of confidence intervals with 95% expected coverage.
Code
mytest
Output
$properties
$properties$effect_size_name
[1] "mean"
$properties$alpha
[1] 0.05
$properties$interval_null
[1] FALSE
$properties$rope
[1] 0 0
$properties$rope_units
[1] "raw"
$point_null
test_type outcome_variable_name effect null_words confidence
1 Nil Hypothesis Test transcription Laptop ‒ Pen 0.00 95
LL UL CI CI_compare
1 2.685265 8.729915 95% CI [2.685265, 8.729915] The 95% CI does not contain H_0
t df p p_result null_decision
1 3.77382 63 0.0003579282 p < 0.05 Reject H_0
conclusion significant
1 At α = 0.05, 0.00 is not a plausible value of μ_diff TRUE
Code
estimate_99
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = transcription
Grouping variable(s) = condition
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level
1 transcription condition Pen
2 transcription condition Laptop
mean mean_LL mean_UL median median_LL median_UL sd min max
1 8.811765 6.037502 11.58603 8.6 5.969560 11.23044 4.749339 1.0 20.1
2 14.519355 11.613953 17.42476 12.8 8.422996 17.17700 7.285576 1.2 34.7
q1 q3 n missing df mean_SE median_SE
1 5.20 11.275 34 0 63 1.044470 1.021201
2 9.45 17.850 31 0 63 1.093842 1.699260
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison transcription condition Laptop
2 Reference transcription condition Pen
3 Difference transcription condition Laptop ‒ Pen
effect_size LL UL SE df ta_LL ta_UL
1 14.519355 11.613953 17.42476 1.093842 63 11.908346 17.130363
2 8.811765 6.037502 11.58603 1.044470 63 6.318608 11.304922
3 5.707590 1.690390 9.72479 1.512417 63 2.097438 9.317742
-- es_median_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison transcription condition Laptop
2 Reference transcription condition Pen
3 Difference transcription condition Laptop ‒ Pen
effect_size LL UL SE ta_LL ta_UL
1 12.8 8.4229960 17.177004 1.699260 8.8469299 16.753070
2 8.6 5.9695599 11.230440 1.021201 6.2243306 10.975669
3 4.2 -0.9066015 9.306602 1.982508 -0.4120026 8.812003
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 transcription condition Laptop ‒ Pen 0.9259595
LL UL numerator denominator SE df d_biased
1 0.2490821 1.59688 5.70759 6.090252 0.2616245 63 0.9371681
This standardized mean difference is called d_s because the standardizer used was s_p. d_s has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
-- es_mean_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 transcription condition Laptop / Pen 1.647724
LL UL comparison_mean reference_mean
1 1.169397 2.321705 14.51935 8.811765
[1] "This effect-size measure is appropriate only for true ratio scales."
-- es_median_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 transcription condition Laptop / Pen 1.488372
LL UL comparison_median reference_median
1 0.9557473 2.317821 12.8 8.6
[1] "This effect-size measure is appropriate only for true ratio scales."
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Compare estimate_mdiff_two to statpsych::ci.mean2 example
Code
estimate
Output
Analysis of raw data:
Outcome variable(s) = My outcome variable
Grouping variable(s) = My grouping variable
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 My outcome variable My grouping variable Control 10.3
2 My outcome variable My grouping variable Treated 15.4
mean_LL mean_UL sd n df mean_SE
1 8.924592 11.67541 2.15 20 19 0.4807546
2 14.056336 16.74366 2.67 30 29 0.4874731
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison My outcome variable My grouping variable Treated
2 Reference My outcome variable My grouping variable Control
3 Difference My outcome variable My grouping variable Treated ‒ Control
effect_size LL UL SE df ta_LL ta_UL
1 15.4 14.056336 16.743664 0.4874731 29.00000 14.199831 16.600169
2 10.3 8.924592 11.675408 0.4807546 19.00000 9.079132 11.520868
3 5.1 3.260617 6.939383 0.6846568 46.17476 3.450073 6.749927
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 My outcome variable My grouping variable Treated ‒ Control 2.070897
LL UL numerator denominator SE df d_biased
1 1.187684 3.013583 5.1 2.423984 0.5604936 47.99877 2.103974
This standardized mean difference is called d_avg because the standardizer used was s_avg. d_avg has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Compare estimate_mdiff_two to statpsych::ci.median2 example
Code
estimate
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = myoutcome
Grouping variable(s) = mycondition
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 myoutcome mycondition Group 1 34.2
2 myoutcome mycondition Group 2 41.5
mean_LL mean_UL median median_LL median_UL sd min max q1 q3 n
1 28.33027 40.06973 34.5 27.21846 41.78154 5.711587 26 43 29.75 38.50 10
2 34.87072 48.12928 43.0 34.59823 51.40177 6.450667 31 49 36.75 46.75 10
missing df mean_SE median_SE
1 0 9 1.806162 2.826871
2 0 9 2.039880 3.261774
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE df ta_LL ta_UL
1 34.2 28.33027 40.0697304 1.806162 9.00000 29.10403 39.2959748
2 41.5 34.87072 48.1292751 2.039880 9.00000 35.74460 47.2553953
3 -7.3 -15.15592 0.5559194 2.724579 17.73989 -14.26401 -0.3359923
-- es_median_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE ta_LL ta_UL
1 34.5 27.21846 41.781536 2.826871 27.92372 41.076285
2 43.0 34.59823 51.401773 3.261774 35.41198 50.588021
3 -8.5 -19.61803 2.618029 4.316291 -18.54119 1.541194
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 ‒ Group 2 -1.146719
LL UL numerator denominator SE df d_biased
1 -2.448433 0.07467368 -7.3 6.092345 0.6550008 17.73989 -1.198225
This standardized mean difference is called d_avg because the standardizer used was s_avg. d_avg has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
-- es_mean_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 / Group 2 0.8240964
LL UL comparison_mean reference_mean
1 0.6694745 1.01443 34.2 41.5
[1] "This effect-size measure is appropriate only for true ratio scales."
-- es_median_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 / Group 2 0.8023256
LL UL comparison_median reference_median
1 0.5919106 1.08754 34.5 43
[1] "This effect-size measure is appropriate only for true ratio scales."
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Compare estimate_mdiff_two to statpsych::ci.ratio.mean2 and ci.ratio.median2 example
Code
estimate
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = myoutcome
Grouping variable(s) = mycondition
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 myoutcome mycondition Group 1 41.50000
2 myoutcome mycondition Group 2 36.38462
mean_LL mean_UL median median_LL median_UL sd min max q1 q3 n
1 34.87072 48.12928 43 34.59823 51.40177 6.450667 31 49 36.75 46.75 10
2 30.67493 42.09430 37 29.66461 44.33539 6.739664 26 49 32.00 40.00 13
missing df mean_SE median_SE
1 0 9 2.039880 3.261774
2 0 12 1.869247 2.847778
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE df ta_LL ta_UL
1 41.500000 34.870725 48.12928 2.039880 9.00000 35.744605 47.25540
2 36.384615 30.674928 42.09430 1.869247 12.00000 31.373169 41.39606
3 5.115385 -2.760215 12.99098 2.766802 19.92414 -1.881322 12.11209
-- es_median_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE ta_LL ta_UL
1 43 34.598227 51.40177 3.261774 35.411979 50.58802
2 37 29.664610 44.33539 2.847778 30.375078 43.62492
3 6 -5.153373 17.15337 4.330013 -4.073115 16.07312
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 ‒ Group 2 0.7470702
LL UL numerator denominator SE df d_biased
1 -0.3558306 1.890873 5.115385 6.596749 0.517002 20.79173 0.7754403
This standardized mean difference is called d_avg because the standardizer used was s_avg. d_avg has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
-- es_mean_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 / Group 2 1.140592
LL UL comparison_mean reference_mean
1 0.9324275 1.395229 41.5 36.38462
[1] "This effect-size measure is appropriate only for true ratio scales."
-- es_median_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 / Group 2 1.162162
LL UL comparison_median reference_median
1 0.8642465 1.562773 43 37
[1] "This effect-size measure is appropriate only for true ratio scales."
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Code
estimate
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = myoutcome
Grouping variable(s) = mycondition
---Overview---
outcome_variable_name grouping_variable_name grouping_variable_level mean
1 myoutcome mycondition Group 1 23.70000
2 myoutcome mycondition Group 2 25.46154
mean_LL mean_UL median median_LL median_UL sd min max q1 q3 n
1 -2.399473 49.79947 37.5 -0.8577566 75.85776 36.48455 -47 49 31.5 45.5 10
2 8.614096 42.30898 35.0 28.1304096 41.86959 27.87955 -39 49 27.0 40.0 13
missing df mean_SE median_SE
1 0 9 11.537427 19.570644
2 0 12 7.732396 3.504957
-- es_mean_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE df ta_LL ta_UL
1 23.700000 -2.399473 49.79947 11.537427 9.00000 2.550593 44.84941
2 25.461538 8.614096 42.30898 7.732396 12.00000 11.680186 39.24289
3 -1.761538 -31.144112 27.62103 13.888922 16.41673 -25.972286 22.44921
-- es_median_difference --
type outcome_variable_name grouping_variable_name effect
1 Comparison myoutcome mycondition Group 1
2 Reference myoutcome mycondition Group 2
3 Difference myoutcome mycondition Group 1 ‒ Group 2
effect_size LL UL SE ta_LL ta_UL
1 37.5 -0.8577566 75.85776 19.570644 5.309156 69.69084
2 35.0 28.1304096 41.86959 3.504957 29.234858 40.76514
3 2.5 -36.4680480 41.46805 19.882022 -30.203017 35.20302
-- es_smd --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 ‒ Group 2 -0.05195366
LL UL numerator denominator SE df d_biased
1 -0.8920995 0.7850884 -1.761538 32.46838 0.4541995 17.98107 -0.05425397
This standardized mean difference is called d_avg because the standardizer used was s_avg. d_avg has been corrected for bias. Correction for bias can be important when df < 50. See the rightmost column for the biased value.
-- es_mean_ratio --
outcome_variable_name grouping_variable_name effect effect_size
1 myoutcome mycondition Group 1 / Group 2 0.9308157
LL UL comparison_mean reference_mean
1 0.275107 3.149385 23.7 25.46154
[1] "WARNING! Your dataset includes negative values. This effect-size measure is appropriate only for true ratio scales."
-- es_median_ratio --
outcome_variable_name grouping_variable_name effect effect_size LL
1 myoutcome mycondition Group 1 / Group 2 NA NA
UL comparison_median reference_median
1 NA NA NA
[1] "WARNING! Your dataset includes negative values. This effect-size measure is appropriate only for true ratio scales."
Note: LL and UL are lower and upper boundaries of confidence intervals with 95% expected coverage.
Warnings:
* The ratio between group effect size is appropriate only for true ratio scales where values < 0 are impossible. Your data include at least one negative value, so the requested ratio effect size is not reported.
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