From 71c28cb8cca5c81bdaf0438773493a87644e1bdf Mon Sep 17 00:00:00 2001 From: acp29 Date: Sat, 6 Jan 2024 01:30:48 +0000 Subject: [PATCH] update manual --- docs/copying.html | 2 +- docs/description.json | 2 +- docs/function/boot.html | 18 +-- docs/function/boot1way.html | 6 +- docs/function/bootbayes.html | 8 +- docs/function/bootcdf.html | 2 +- docs/function/bootci.html | 34 +++--- docs/function/bootclust.html | 32 +++--- docs/function/bootknife.html | 36 +++--- docs/function/bootlm.html | 152 +++++++++++++++++--------- docs/function/bootmode.html | 6 +- docs/function/bootstrp.html | 98 ++++++++--------- docs/function/bootwild.html | 6 +- docs/function/cor.html | 2 +- docs/function/credint.html | 2 +- docs/function/deffcalc.html | 2 +- docs/function/images/boot1way_601.png | Bin 24421 -> 24313 bytes docs/function/images/boot1way_701.png | Bin 24385 -> 24385 bytes docs/function/randtest2.html | 12 +- docs/function/sampszcalc.html | 4 +- docs/function/smoothmad.html | 2 +- docs/function/smoothmedian.html | 2 +- docs/function_reference.html | 4 +- docs/index.html | 2 +- docs/readme.html | 4 +- 25 files changed, 246 insertions(+), 192 deletions(-) diff --git a/docs/copying.html b/docs/copying.html index 9935d7e9..1c813d53 100644 --- a/docs/copying.html +++ b/docs/copying.html @@ -3,7 +3,7 @@ - + diff --git a/docs/description.json b/docs/description.json index 59f75668..cdaaf151 100644 --- a/docs/description.json +++ b/docs/description.json @@ -1,7 +1,7 @@ { "generator": "generate_html", "generator_version": "0.3.3", - "date_generated": "2024-01-04", + "date_generated": "2024-01-06", "package": { "name": "statistics-resampling", diff --git a/docs/function/boot.html b/docs/function/boot.html index c255f1c5..3a9879d9 100644 --- a/docs/function/boot.html +++ b/docs/function/boot.html @@ -3,7 +3,7 @@ - + @@ -43,6 +43,9 @@ are chosen by balanced bootstrap resampling as described above [1-3]. Balanced resampling only applies when NBOOT > 1. + Note that the values of N and NBOOT map onto int32 data types in the + boot MEX file. Therefore, these values must never exceed (2^31)-1. + 'BOOTSAM = boot (..., NBOOT, LOO)' sets the resampling method. If LOO is false, the resampling method used is balanced bootstrap resampling. If LOO is true, the resampling method used is balanced bootknife @@ -72,6 +75,7 @@ corresponding index (or element in X) is represented in BOOTSAM. Therefore, the sum of WEIGHTS must equal N * NBOOT. + Bibliography: [1] Efron, and Tibshirani (1993) An Introduction to the Bootstrap. New York, NY: Chapman & Hall @@ -111,9 +115,9 @@

Demonstration 1

Produces the following output

ans =
 
-   3   3   1   2   1   3   2   3   2   1   1   3   2   1   3   3   2   2   2   3
-   3   3   1   2   1   1   1   2   3   1   1   2   1   2   3   3   1   1   3   1
-   3   2   2   3   2   2   2   1   3   1   2   3   2   3   2   1   1   1   3   2
+ 3 1 1 2 3 3 2 1 2 2 3 1 3 1 3 1 1 3 3 3 + 2 2 3 3 1 1 3 1 2 1 1 2 2 2 2 2 3 3 2 3 + 1 2 1 3 1 1 1 1 2 2 3 1 3 2 2 2 3 1 2 3

Demonstration 2

@@ -125,9 +129,9 @@

Demonstration 2

Produces the following output

ans =
 
-   3   3   1   3   3   2   2   1   1   2   1   1   3   3   1   3   1   2   2   1
-   2   1   2   3   3   2   3   3   1   3   1   1   3   3   2   3   1   2   2   1
-   3   3   1   2   1   2   2   1   1   2   3   2   2   1   2   2   3   2   3   1
+ 3 3 1 2 3 1 2 1 2 2 1 1 3 1 2 2 3 1 1 1 + 3 3 2 3 3 2 2 1 2 2 1 2 3 1 2 3 3 2 3 1 + 3 1 1 2 3 2 3 1 1 3 3 2 3 1 2 3 1 2 1 2

Demonstration 3

diff --git a/docs/function/boot1way.html b/docs/function/boot1way.html index dfd77782..e7b92337 100644 --- a/docs/function/boot1way.html +++ b/docs/function/boot1way.html @@ -3,7 +3,7 @@ - + @@ -472,7 +472,7 @@

Demonstration 6

----------------------------------------------------------------------------- | Comparison | Test # | Ref # | Difference | t | p | |------------|------------|------------|------------|------------|----------| -| 1 | 2 | 1 | +0.1328 | +0.29 | .776 | +| 1 | 2 | 1 | +0.004848 | +0.01 | .996 | ----------------------------------------------------------------------------- | GROUP # | GROUP label | N | @@ -517,7 +517,7 @@

Demonstration 7

----------------------------------------------------------------------------- | Comparison | Test # | Ref # | Difference | t | p | |------------|------------|------------|------------|------------|----------| -| 1 | 2 | 1 | -0.3151 | -0.56 | .431 | +| 1 | 2 | 1 | -0.2044 | -0.39 | .603 | ----------------------------------------------------------------------------- | GROUP # | GROUP label | N | diff --git a/docs/function/bootbayes.html b/docs/function/bootbayes.html index cb40b2f3..fb60494a 100644 --- a/docs/function/bootbayes.html +++ b/docs/function/bootbayes.html @@ -3,7 +3,7 @@ - + @@ -185,7 +185,7 @@

Demonstration 1

Posterior Statistics: original bias median stdev CI_lower CI_upper - +184.5 +0.01592 +184.4 1.325 +182.0 +187.2 + +184.5 -0.01585 +184.5 1.311 +182.0 +187.1

Demonstration 2

@@ -221,8 +221,8 @@

Demonstration 2

Posterior Statistics: original bias median stdev CI_lower CI_upper - +175.5 -0.01061 +175.5 2.414 +171.1 +180.5 - +0.1904 -0.0007931 +0.1917 0.08040 +0.04178 +0.3556 + +175.5 -0.09230 +175.4 2.415 +171.1 +180.4 + +0.1904 +0.002915 +0.1921 0.07944 +0.04305 +0.3495

Package: statistics-resampling

diff --git a/docs/function/bootcdf.html b/docs/function/bootcdf.html index 646816c9..3e38e276 100644 --- a/docs/function/bootcdf.html +++ b/docs/function/bootcdf.html @@ -3,7 +3,7 @@ - + diff --git a/docs/function/bootci.html b/docs/function/bootci.html index f48758dc..eaef89e5 100644 --- a/docs/function/bootci.html +++ b/docs/function/bootci.html @@ -3,7 +3,7 @@ - + @@ -182,8 +182,8 @@

Demonstration 1

Produces the following output

ci =
 
-   23.540
-   34.574
+ 23.616 + 34.358

Demonstration 2

@@ -201,8 +201,8 @@

Demonstration 2

Produces the following output

ci =
 
-   23.886
-   34.390
+ 23.975 + 34.269

Demonstration 3

@@ -221,8 +221,8 @@

Demonstration 3

Produces the following output

ci =
 
-   24.710
-   37.094
+ 25.040 + 36.477

Demonstration 4

@@ -238,8 +238,8 @@

Demonstration 4

Produces the following output

ci =
 
-    96.788
-   237.389
+ 96.629 + 235.910

Demonstration 5

@@ -255,8 +255,8 @@

Demonstration 5

Produces the following output

ci =
 
-   116.08
-   263.28
+ 117.01 + 260.73

Demonstration 6

@@ -275,8 +275,8 @@

Demonstration 6

Produces the following output

ci =
 
-   116.56
-   293.82
+ 108.55 + 297.71

Demonstration 7

@@ -295,8 +295,8 @@

Demonstration 7

Produces the following output

ci =
 
-   112.32
-   280.18
+ 111.53 + 268.13

Demonstration 8

@@ -316,8 +316,8 @@

Demonstration 8

Produces the following output

ci =
 
-   0.5174
-   0.8637
+ 0.5050 + 0.8633

Demonstration 9

diff --git a/docs/function/bootclust.html b/docs/function/bootclust.html index 67befc67..d1811aa6 100644 --- a/docs/function/bootclust.html +++ b/docs/function/bootclust.html @@ -3,7 +3,7 @@ - + @@ -172,7 +172,7 @@

Demonstration 1

Bootstrap Statistics: original bias std_error CI_lower CI_upper - +29.65 -4.619e-14 +2.638 +23.27 +34.70 + +29.65 +1.421e-14 +2.547 +23.48 +34.49

Demonstration 2

@@ -197,11 +197,11 @@

Demonstration 2

Resampling method: Balanced, bootstrap cluster resampling Number of resamples: 1999 Confidence interval (CI) type: Expanded bias-corrected and accelerated (BCa) - Nominal coverage (and the percentiles used): 95% (1.3%, 98.9%) + Nominal coverage (and the percentiles used): 95% (1.2%, 98.9%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +29.65 -0.03867 +2.896 +23.07 +36.16 + +29.65 -0.03188 +2.912 +23.04 +35.99

Demonstration 3

@@ -228,7 +228,7 @@

Demonstration 3

Bootstrap Statistics: original bias std_error CI_lower CI_upper - +171.5 -6.654 +42.63 +96.46 +234.8 + +171.5 -6.354 +42.51 +97.80 +236.1

Demonstration 4

@@ -257,7 +257,7 @@

Demonstration 4

Bootstrap Statistics: original bias std_error CI_lower CI_upper - +171.5 -9.393 +34.16 +102.6 +215.7 + +171.5 -9.381 +33.37 +104.1 +214.3

Demonstration 5

@@ -279,11 +279,11 @@

Demonstration 5

Resampling method: Balanced, bootstrap cluster resampling Number of resamples: 1999 Confidence interval (CI) type: Bias-corrected and accelerated (BCa) - Nominal coverage (and the percentiles used): 90% (11.9%, 98.7%) + Nominal coverage (and the percentiles used): 90% (10.7%, 98.4%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +171.5 -6.689 +41.19 +115.9 +258.5 + +171.5 -6.485 +41.58 +112.9 +252.7

Demonstration 6

@@ -307,11 +307,11 @@

Demonstration 6

Resampling method: Balanced, bootstrap cluster resampling Number of resamples: 1999 Confidence interval (CI) type: Bias-corrected and accelerated (BCa) - Nominal coverage (and the percentiles used): 90% (13.2%, 98.7%) + Nominal coverage (and the percentiles used): 90% (12.5%, 98.6%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +171.5 -9.602 +34.15 +122.7 +231.3 + +171.5 -9.414 +33.59 +121.9 +231.1

Demonstration 7

@@ -336,8 +336,8 @@

Demonstration 7

Bootstrap Statistics: original bias std_error CI_lower CI_upper - -0.05747 +0.009976 +0.2228 -0.4408 +0.2894 - -0.2821 +0.009019 +0.2021 -0.5871 +0.07347 + -0.2246 +0.003490 +0.2145 -0.6148 +0.09204 + -0.09154 +0.0006074 +0.2059 -0.4611 +0.2211

Demonstration 8

@@ -363,8 +363,8 @@

Demonstration 8

Bootstrap Statistics: original bias std_error CI_lower CI_upper - -0.1846 -0.007533 +0.08858 -0.3732 -0.07310 - -0.001791 +0.03147 +0.1574 -0.2306 +0.2747 + +0.2463 +0.02234 +0.2264 -0.08453 +0.6083 + +0.1312 -0.02858 +0.2918 -0.3834 +0.4772

Demonstration 9

@@ -390,11 +390,11 @@

Demonstration 9

Resampling method: Balanced, bootstrap cluster resampling Number of resamples: 1999 Confidence interval (CI) type: Bias-corrected and accelerated (BCa) - Nominal coverage (and the percentiles used): 95% (2.2%, 97.2%) + Nominal coverage (and the percentiles used): 95% (1.9%, 97.0%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +0.7764 -0.02400 +0.1423 +0.4177 +0.9997 + +0.7764 -0.02475 +0.1457 +0.4011 +1.000

Package: statistics-resampling

diff --git a/docs/function/bootknife.html b/docs/function/bootknife.html index 4aeef70b..32f97d91 100644 --- a/docs/function/bootknife.html +++ b/docs/function/bootknife.html @@ -3,7 +3,7 @@ - + @@ -221,11 +221,11 @@

Demonstration 1

Number of resamples (outer): 1999 Number of resamples (inner): 0 Confidence interval (CI) type: Expanded bias-corrected and accelerated (BCa) - Nominal coverage (and the percentiles used): 95% (1.3%, 97.1%) + Nominal coverage (and the percentiles used): 95% (1.4%, 97.4%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +29.65 +4.974e-14 +2.598 +23.62 +34.44 + +29.65 +7.105e-15 +2.715 +23.49 +34.75

Demonstration 2

@@ -250,11 +250,11 @@

Demonstration 2

Number of resamples (outer): 1999 Number of resamples (inner): 199 Confidence interval (CI) type: Calibrated percentile - Nominal coverage (and the percentiles used): 95% (1.0%, 96.9%) + Nominal coverage (and the percentiles used): 95% (1.2%, 97.2%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +29.65 -1.421e-14 +2.760 +23.37 +34.56 + +29.65 +4.974e-14 +2.624 +23.71 +34.47

Demonstration 3

@@ -280,11 +280,11 @@

Demonstration 3

Number of resamples (outer): 1999 Number of resamples (inner): 199 Confidence interval (CI) type: Calibrated percentile - Nominal coverage (and the percentiles used): 95% (2.4%, 97.7%) + Nominal coverage (and the percentiles used): 95% (1.9%, 97.8%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +30.86 -0.01129 +2.963 +24.87 +36.93 + +30.86 -0.06469 +2.926 +24.57 +36.82

Demonstration 4

@@ -312,7 +312,7 @@

Demonstration 4

Bootstrap Statistics: original bias std_error CI_lower CI_upper - +171.5 -7.305 +43.08 +93.64 +237.0 + +171.5 -6.830 +43.20 +95.90 +237.0

Demonstration 5

@@ -335,11 +335,11 @@

Demonstration 5

Number of resamples (outer): 1999 Number of resamples (inner): 0 Confidence interval (CI) type: Bias-corrected and accelerated (BCa) - Nominal coverage (and the percentiles used): 90% (11.8%, 98.6%) + Nominal coverage (and the percentiles used): 90% (12.4%, 98.8%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +171.5 -6.845 +43.09 +113.0 +260.0 + +171.5 -7.246 +42.88 +114.1 +262.4

Demonstration 6

@@ -365,11 +365,11 @@

Demonstration 6

Number of resamples (outer): 1999 Number of resamples (inner): 199 Confidence interval (CI) type: Calibrated percentile (equal-tailed) - Nominal coverage (and the percentiles used): 90% (1.8%, 98.2%) + Nominal coverage (and the percentiles used): 90% (1.9%, 98.1%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +171.5 -6.655 +45.96 +75.68 +256.8 + +171.5 -7.360 +46.51 +80.98 +254.0

Demonstration 7

@@ -394,11 +394,11 @@

Demonstration 7

Number of resamples (outer): 1999 Number of resamples (inner): 199 Confidence interval (CI) type: Calibrated percentile - Nominal coverage (and the percentiles used): 90% (10.7%, 99.5%) + Nominal coverage (and the percentiles used): 90% (10.3%, 99.5%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +171.5 -7.673 +47.50 +109.8 +283.3 + +171.5 -7.631 +48.06 +108.1 +281.9

Demonstration 8

@@ -424,8 +424,8 @@

Demonstration 8

Bootstrap Statistics: original bias std_error CI_lower CI_upper - +0.1791 -0.0002310 +0.2001 -0.1727 +0.4907 - +0.08737 -0.002962 +0.2226 -0.2714 +0.4468 + +0.2121 +0.0006564 +0.1773 -0.09501 +0.4908 + -0.1055 +0.05113 +0.2565 -0.4257 +0.3830

Demonstration 9

@@ -451,11 +451,11 @@

Demonstration 9

Number of resamples (outer): 1999 Number of resamples (inner): 0 Confidence interval (CI) type: Bias-corrected and accelerated (BCa) - Nominal coverage (and the percentiles used): 95% (0.5%, 93.5%) + Nominal coverage (and the percentiles used): 95% (0.5%, 93.3%) Bootstrap Statistics: original bias std_error CI_lower CI_upper - +0.7764 -0.005818 +0.1392 +0.3148 +0.9490 + +0.7764 -0.005684 +0.1374 +0.3208 +0.9442

Demonstration 10

diff --git a/docs/function/bootlm.html b/docs/function/bootlm.html index ef289113..1ddf7e8d 100644 --- a/docs/function/bootlm.html +++ b/docs/function/bootlm.html @@ -3,7 +3,7 @@ - + @@ -395,7 +395,7 @@ - 'MSE': Mean Squared Error The ANOVA implemented uses sequential (type I) sums-of-squares and so - the results and their interpretation depend on the order of predictors + the results and their interpretation depend on the order** of predictors in the GROUP variable (when the design is not balanced). Thus, the null model used for comparison for each model is the model listed directly above it in AOVSTAT; for the first model, the null model is the @@ -406,6 +406,10 @@ model. Computations of the statistics in AOVSTAT are compatible with the 'clustid' and 'blocksz' options. + ** See demo 6 for an example of how to obtain results for ANOVA using + type II sums-of-squares, which test hypotheses that give results + invariant to the order of the predictors. + '[STATS, BOOTSTAT, AOVSTAT, PRED_ERR] = bootlm (...)' also computes refined bootstrap estimates of prediction error* and returns the derived statistics in a structure with the following fields: @@ -475,7 +479,7 @@

Demonstration 1

name mean CI_lower CI_upper p-adj -------------------------------------------------------------------------------- -female - male +10.80 -8.860 +30.46 .247 +female - male +10.80 -8.431 +30.03 .247 MODEL FORMULA (based on Wilkinson's notation): @@ -486,8 +490,8 @@

Demonstration 1

name mean CI_lower CI_upper N -------------------------------------------------------------------------------- -male +44.20 +32.49 +53.54 5 -female +55.00 +42.06 +67.63 6 +male +44.20 +32.61 +53.28 5 +female +55.00 +42.59 +67.90 6

and the following figure

@@ -532,7 +536,7 @@

Demonstration 2

name mean CI_lower CI_upper p-adj -------------------------------------------------------------------------------- -after - before +1.460 +0.6443 +2.276 .003 +after - before +1.460 +0.6548 +2.265 .003 MODEL FORMULA (based on Wilkinson's notation): @@ -543,8 +547,8 @@

Demonstration 2

name mean CI_lower CI_upper N -------------------------------------------------------------------------------- -before +4.560 +4.099 +4.977 5 -after +6.020 +5.564 +6.455 5 +before +4.560 +4.100 +4.995 5 +after +6.020 +5.605 +6.485 5

and the following figure

@@ -586,9 +590,9 @@

Demonstration 3

name mean CI_lower CI_upper p-adj -------------------------------------------------------------------------------- -st - al1 +7.000 +3.922 +10.08 <.001 -st - al2 +5.000 +2.565 +7.435 <.001 -al1 - al2 -2.000 -4.911 +0.9107 .175 +st - al1 +7.000 +3.878 +10.12 <.001 +st - al2 +5.000 +2.539 +7.461 <.001 +al1 - al2 -2.000 -4.897 +0.8972 .172 MODEL FORMULA (based on Wilkinson's notation): @@ -599,9 +603,9 @@

Demonstration 3

name mean CI_lower CI_upper N -------------------------------------------------------------------------------- -st +84.00 +82.10 +85.64 8 -al1 +77.00 +74.97 +79.42 6 -al2 +79.00 +77.65 +80.39 6 +st +84.00 +82.16 +85.67 8 +al1 +77.00 +74.91 +79.46 6 +al2 +79.00 +77.70 +80.41 6

and the following figure

@@ -649,9 +653,9 @@

Demonstration 4

name mean CI_lower CI_upper p-adj -------------------------------------------------------------------------------- -1 - 2 -2.000 -2.725 -1.275 <.001 -1 - 5 -3.200 -3.852 -2.548 <.001 -2 - 5 -1.200 -2.081 -0.3192 .012 +1 - 2 -2.000 -2.730 -1.270 <.001 +1 - 5 -3.200 -3.861 -2.539 <.001 +2 - 5 -1.200 -2.075 -0.3248 .014 MODEL FORMULA (based on Wilkinson's notation): @@ -662,9 +666,9 @@

Demonstration 4

name mean CI_lower CI_upper N -------------------------------------------------------------------------------- -1 +11.00 +10.65 +11.36 10 -2 +13.00 +12.52 +13.47 10 -5 +14.20 +13.76 +14.64 10 +1 +11.00 +10.65 +11.37 10 +2 +13.00 +12.53 +13.49 10 +5 +14.20 +13.72 +14.62 10

and the following figure

@@ -735,12 +739,12 @@

Demonstration 5

name coeff CI_lower CI_upper p-val -------------------------------------------------------------------------------- -(Intercept) +5.667 +4.790 +6.543 <.001 -brands_1 -1.333 -1.892 -0.7744 .013 +(Intercept) +5.667 +4.793 +6.540 <.001 +brands_1 -1.333 -1.910 -0.7565 .013 brands_2 -2.167 -3.122 -1.211 <.001 -popper_1 +1.167 +0.6065 +1.727 .015 -brands:popper_1 -0.3333 -1.084 +0.4177 .335 -brands:popper_2 -0.1667 -1.259 +0.9259 .727 +popper_1 +1.167 +0.5984 +1.735 .017 +brands:popper_1 -0.3333 -1.096 +0.4298 .345 +brands:popper_2 -0.1667 -1.269 +0.9361 .725 MODEL FORMULA (based on Wilkinson's notation): @@ -751,9 +755,9 @@

Demonstration 5

name mean CI_lower CI_upper p-adj -------------------------------------------------------------------------------- -Gourmet - National +1.500 +1.130 +1.870 <.001 -Gourmet - Generic +2.250 +1.713 +2.787 <.001 -National - Generic +0.7500 +0.2086 +1.291 .010 +Gourmet - National +1.500 +1.125 +1.875 <.001 +Gourmet - Generic +2.250 +1.707 +2.793 <.001 +National - Generic +0.7500 +0.2099 +1.290 .010 MODEL FORMULA (based on Wilkinson's notation): @@ -764,9 +768,9 @@

Demonstration 5

name mean CI_lower CI_upper N -------------------------------------------------------------------------------- -Gourmet +6.250 +6.065 +6.442 6 -National +4.750 +4.564 +4.941 6 -Generic +4.000 +3.674 +4.314 6 +Gourmet +6.250 +6.063 +6.437 6 +National +4.750 +4.565 +4.937 6 +Generic +4.000 +3.679 +4.326 6 MODEL FORMULA (based on Wilkinson's notation): @@ -777,7 +781,7 @@

Demonstration 5

name mean CI_lower CI_upper p-adj -------------------------------------------------------------------------------- -oil - air -1.000 -1.373 -0.6269 <.001 +oil - air -1.000 -1.393 -0.6074 <.001 MODEL FORMULA (based on Wilkinson's notation): @@ -788,8 +792,8 @@

Demonstration 5

name mean CI_lower CI_upper N -------------------------------------------------------------------------------- -oil +4.500 +4.312 +4.686 9 -air +5.500 +5.311 +5.686 9 +oil +4.500 +4.322 +4.694 9 +air +5.500 +5.322 +5.696 9

and the following figure

@@ -814,10 +818,12 @@

Demonstration 6

'm' 'm' 'm' 'm' 'm' 'm' 'm' 'm' 'm' 'm'}'; degree = [1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0]'; - ## ANOVA (including the main effect of gender averaged over levels of degree) + ## ANOVA (including the main effect of gender averaged over levels of degree). + ## We are setting a random seed here for comparison between results for + ## different models. [STATS, BOOTSTAT, AOVSTAT] = bootlm (salary, {degree, gender}, 'model', ... 'full', 'display', 'off', 'varnames', ... - {'degree', 'gender'}); + {'degree', 'gender'}, 'seed', 1); fprintf ('ANOVA SUMMARY with gender averaged over levels of degree\n') for i = 1:numel(AOVSTAT.F) @@ -826,10 +832,13 @@

Demonstration 6

AOVSTAT.PVAL(i), AOVSTAT.MODEL{i}); end - ## ANOVA (including the main effect of degree averaged over levels of gender) + ## ANOVA (including the main effect of degree averaged over levels of gender). + ## We are setting a random seed here for comparison between results for + ## different models. Note that the result for the interaction is not affected + ## by the order of the predictors. [STATS, BOOTSTAT, AOVSTAT] = bootlm (salary, {gender, degree}, 'model', ... 'full', 'display', 'off', 'varnames', ... - {'gender', 'degree'}); + {'gender', 'degree'}, 'seed', 1); fprintf ('\nANOVA SUMMARY with degree averaged over levels of gender\n') for i = 1:numel(AOVSTAT.F) @@ -838,6 +847,43 @@

Demonstration 6

AOVSTAT.PVAL(i), AOVSTAT.MODEL{i}); end + ## Since the interaction term (F(1,18) = 0.42) was not significant (p > 0.1), + ## we might rather consider the hypotheses tested using type II sums-of- + ## squares without the interaction, which do not depend on the order and have + ## more power respectively. This is easy to achieve with 2 predictors, by + ## repeating the 'bootlm' commands with different predictors added last to + ## the model (as above) but without the interaction (i.e. setting 'model', + ## 'linear'). We then take the statistics for the last main effect listed + ## in each of the ANOVA tables - these then correspond to the ANOVA test for + ## the respective predictor with type II sums-of-squares. For example: + + [~, ~, AOVSTAT1] = bootlm (salary, {degree, gender}, 'model', ... + 'linear', 'display', 'off', 'varnames', ... + {'degree', 'gender'}, 'seed', 1); + + fprintf ('\nANOVA SUMMARY (with type II sums-of-squares for main effects)\n') + fprintf ('F(%u,%u) = %.2f, p = %.3g for the model: %s (Gender)\n', ... + AOVSTAT1.DF(2), AOVSTAT1.DFE, AOVSTAT1.F(2), ... + AOVSTAT1.PVAL(2), AOVSTAT1.MODEL{2}); + + [~, ~, AOVSTAT2] = bootlm (salary, {gender, degree}, 'model', ... + 'linear', 'display', 'off', 'varnames', ... + {'gender', 'degree'}, 'seed', 1); + + fprintf ('F(%u,%u) = %.2f, p = %.3g for the model: %s (Degree)\n', ... + AOVSTAT2.DF(2), AOVSTAT2.DFE, AOVSTAT2.F(2), ... + AOVSTAT2.PVAL(2), AOVSTAT2.MODEL{2}); + + ## Here is the output from 'anovan' for comparison: + ## ANOVA TABLE (Type II sums-of-squares): + ## + ## Source Sum Sq. d.f. Mean Sq. R Sq. F Prob>F + ## -------------------------------------------------------------------------- + ## gender 30.462 1 30.462 0.373 11.31 .003 + ## degree 272.39 1 272.39 0.842 101.13 <.001 + ## Error 51.175 19 2.6934 + ## Total 323.86 21 + ## Check regression coefficient corresponding to gender x degree interaction STATS = bootlm (salary, {gender, degree}, 'model', 'full', ... 'display', 'on', 'varnames', ... @@ -873,13 +919,17 @@

Demonstration 6

Produces the following output

ANOVA SUMMARY with gender averaged over levels of degree
 F(1,18) = 87.20, p = 0.0001 for the model: salary ~ 1 + degree
-F(1,18) = 10.97, p = 0.00474 for the model: salary ~ 1 + degree + gender
-F(1,18) = 0.42, p = 0.574 for the model: salary ~ 1 + degree + gender + degree:gender
+F(1,18) = 10.97, p = 0.00495 for the model: salary ~ 1 + degree + gender
+F(1,18) = 0.42, p = 0.567 for the model: salary ~ 1 + degree + gender + degree:gender
 
 ANOVA SUMMARY with degree averaged over levels of gender
-F(1,18) = 0.11, p = 0.747 for the model: salary ~ 1 + gender
+F(1,18) = 0.11, p = 0.752 for the model: salary ~ 1 + gender
 F(1,18) = 98.06, p = 0.0001 for the model: salary ~ 1 + gender + degree
-F(1,18) = 0.42, p = 0.564 for the model: salary ~ 1 + gender + degree + gender:degree
+F(1,18) = 0.42, p = 0.567 for the model: salary ~ 1 + gender + degree + gender:degree
+
+ANOVA SUMMARY (with type II sums-of-squares for main effects)
+F(1,19) = 11.31, p = 0.00481 for the model: salary ~ 1 + degree + gender (Gender)
+F(1,19) = 101.13, p = 0.0001 for the model: salary ~ 1 + gender + degree (Degree)
 
 MODEL FORMULA (based on Wilkinson's notation):
 
@@ -890,9 +940,9 @@ 
Demonstration 6

 name                                   coeff       CI_lower    CI_upper    p-val
 --------------------------------------------------------------------------------
 (Intercept)                            +25.00      +23.67      +26.33      <.001
-gender_1                               +2.000      -0.9634     +4.963       .220
-degree_1                               -8.000      -10.78      -5.221      <.001
-gender:degree_1                        +1.000      -2.917      +4.917       .579
+gender_1                               +2.000      -0.9460     +4.946       .216
+degree_1                               -8.000      -10.75      -5.254      <.001
+gender:degree_1                        +1.000      -2.877      +4.877       .578
 
 
 MODEL FORMULA (based on Wilkinson's notation):
@@ -903,7 +953,7 @@ 
Demonstration 6

 
 name                                   mean        CI_lower    CI_upper    p-adj
 --------------------------------------------------------------------------------
-m - f                                  +2.500      +0.5893     +4.411       .014
+m - f                                  +2.500      +0.5502     +4.450       .013
 
 
 MODEL FORMULA (based on Wilkinson's notation):
@@ -914,8 +964,8 @@ 
Demonstration 6

 
 name                                   mean        CI_lower    CI_upper        N
 --------------------------------------------------------------------------------
-f                                      +21.00      +20.01      +21.99         12
-m                                      +23.50      +22.51      +24.46         10
+f                                      +21.00      +20.04      +22.03         12
+m                                      +23.50      +22.51      +24.48         10
 
 
 MODEL FORMULA (based on Wilkinson's notation):
@@ -926,7 +976,7 @@ 
Demonstration 6

 
 name                                   mean        CI_lower    CI_upper    p-adj
 --------------------------------------------------------------------------------
-0 - 1                                  -7.500      -9.429      -5.571      <.001
+0 - 1                                  -7.500      -9.422      -5.578      <.001
 
 
 MODEL FORMULA (based on Wilkinson's notation):
@@ -937,8 +987,8 @@ 
Demonstration 6

 
 name                                   mean        CI_lower    CI_upper        N
 --------------------------------------------------------------------------------
-1                                      +26.00      +25.03      +26.97         11
-0                                      +18.50      +17.53      +19.52         11
+1 +26.00 +25.06 +27.02 11 +0 +18.50 +17.56 +19.54 11

and the following figure

diff --git a/docs/function/bootmode.html b/docs/function/bootmode.html index 64c0980b..dc59676b 100644 --- a/docs/function/bootmode.html +++ b/docs/function/bootmode.html @@ -3,7 +3,7 @@ - + @@ -147,9 +147,9 @@

Demonstration 1

Produces the following output

ans = Summary of results:
 
-ans = H1 is 1 with p = 0 so reject the null hypothesisthat there is 1 mode
+ans = H1 is 1 with p = 0.0005 so reject the null hypothesisthat there is 1 mode
 
-ans = H2 is 0 with p = 0.328 so accept the null hypothesis that there are 2 modes
+ans = H2 is 0 with p = 0.341 so accept the null hypothesis that there are 2 modes

Package: statistics-resampling

diff --git a/docs/function/bootstrp.html b/docs/function/bootstrp.html index 392534d4..37434fcf 100644 --- a/docs/function/bootstrp.html +++ b/docs/function/bootstrp.html @@ -3,7 +3,7 @@ - + @@ -103,58 +103,58 @@

Demonstration 1

Produces the following output

bootstat =
 
-   27.231
-   30.462
-   26.846
-   29.654
-   31.154
-   29.769
-   30.308
-   31.231
-   30.731
-   31.000
-   27.692
-   29.346
-   29.923
-   34.731
-   26.462
-   29.269
-   28.308
-   28.115
-   27.231
-   28.385
-   28.462
+   30.385
+   26.577
+   32.962
+   26.885
+   28.962
+   27.385
+   29.538
+   28.615
+   36.269
+   29.192
+   36.192
+   35.346
+   30.923
+   31.423
+   30.231
+   25.692
+   28.577
    27.038
+   26.269
+   31.423
+   30.154
+   29.654
+   28.577
+   32.154
    28.385
-   28.962
-   25.808
-   27.615
+   32.615
+   24.846
    32.269
-   31.231
-   36.231
-   35.538
-   28.692
-   30.000
-   31.615
-   29.423
-   28.846
-   26.000
-   31.231
-   35.423
-   27.615
-   28.538
-   27.385
-   30.769
-   26.462
-   25.192
-   33.769
-   27.846
-   32.462
-   31.538
-   30.885
+   25.577
    29.615
-
-ans = 2.5580
+ 26.923 + 27.038 + 26.731 + 33.923 + 31.962 + 26.538 + 26.846 + 29.769 + 27.000 + 26.731 + 29.231 + 30.885 + 31.077 + 30.000 + 29.115 + 31.769 + 32.423 + 30.692 + 29.231 + 31.077 + +ans = 2.7164

Package: statistics-resampling

diff --git a/docs/function/bootwild.html b/docs/function/bootwild.html index 8ccdbc4f..9ca508c2 100644 --- a/docs/function/bootwild.html +++ b/docs/function/bootwild.html @@ -3,7 +3,7 @@ - + @@ -210,8 +210,8 @@

Demonstration 2

Test Statistics: original std_err CI_lower CI_upper t-stat p-val FPR - +175.5 +2.502 +169.9 +181.2 +70.1 <.001 .010 - +0.1904 +0.08261 +0.009537 +0.3713 +2.31 .040 .259 + +175.5 +2.502 +169.6 +181.4 +70.1 <.001 .010 + +0.1904 +0.08261 -0.003357 +0.3842 +2.31 .052 .296

Package: statistics-resampling

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f00VvJ&PU{1ai+ zhLPS1jo*jMmNN+P4<@b_3TPgYi=7QPzv5+Zh=}u?;*uSK{;>l!%HE zB%{s-52~IsRU_B9)Q^c|5jn}J;bG%!)pSCHneYCM?)Gy$8E1Z`EG{nrrBnJGc zqil@BZmuCOBJe?06qUdrvqGaXu&x;+zJb6+)Q~`|Su8mFQt2w%QRA#q2RY4>DapeGP1}I^g)t1lZ^tV)-BxUz?aQ{53F_!Y;))aBc(yFXpRbTbIMa_s?w`}XX6_de+! zN-Dm1CLkWpcs!=VI4cM-i1nEkFAAU;K++T!2xDE5yXNIbGzN83xT9Ff8#`hG@#s)I&q*=XJupzy+fu*Z62 zSF-K&h`vYhOA&#yVgcfHjM7XGWG45kQX1bP#J)`zE~sHX`@%dS#0 zGWHA(YA>s1UqLe7N}O5?rdeJEEcAbK#C-7L3S0M(Nh9BvxA1<_Nh$f`DUui6{})qz Bw2}Y- diff --git a/docs/function/randtest2.html b/docs/function/randtest2.html index 94f9a1c2..56149aab 100644 --- a/docs/function/randtest2.html +++ b/docs/function/randtest2.html @@ -3,7 +3,7 @@ - + @@ -150,9 +150,9 @@

Demonstration 1

@(x, y) log (var (y) ./ var (x)))

Produces the following output

-
pval = 0.3402
-pval = 0.2822
-pval = 0.3086
+
pval = 0.3632
+pval = 0.2718
+pval = 0.3195

Demonstration 2

@@ -203,7 +203,7 @@

Demonstration 3

pval = randtest2 ([X GX], [Y GY], false, 5000)

Produces the following output

-
pval = 1.2000e-03
+
pval = 9.0000e-04
 pval = 0.2000

Demonstration 4

@@ -225,7 +225,7 @@

Demonstration 4

pval = randtest2 ([X GX], [Y GY], true, 5000)

Produces the following output

-
pval = 1.8000e-03
+
pval = 1.5000e-03
 pval = 0.2500

 
 
diff --git a/docs/function/sampszcalc.html b/docs/function/sampszcalc.html
index 43cc7913..27ff0ed2 100644
--- a/docs/function/sampszcalc.html
+++ b/docs/function/sampszcalc.html
@@ -3,7 +3,7 @@
 
   
   
-  
+  
   
   
   
@@ -20,7 +20,7 @@
 

 
 
 Performs sample size calculations, with optional correction for the design
- effect deviating from ideal unity.
+ effect deviating from unity.
 
  -- Function File: N = sampszcalc (TESTTYPE, EFFSZ)
  -- Function File: N = sampszcalc (TESTTYPE, EFFSZ, POW)
diff --git a/docs/function/smoothmad.html b/docs/function/smoothmad.html
index ea6646b1..b83ef199 100644
--- a/docs/function/smoothmad.html
+++ b/docs/function/smoothmad.html
@@ -3,7 +3,7 @@
 
   
   
-  
+  
   
   
   
diff --git a/docs/function/smoothmedian.html b/docs/function/smoothmedian.html
index 620c876f..cf6dc441 100644
--- a/docs/function/smoothmedian.html
+++ b/docs/function/smoothmedian.html
@@ -3,7 +3,7 @@
 
   
   
-  
+  
   
   
   
diff --git a/docs/function_reference.html b/docs/function_reference.html
index eef1e543..65528392 100644
--- a/docs/function_reference.html
+++ b/docs/function_reference.html
@@ -3,7 +3,7 @@
 
   
   
-  
+  
   
   
   
@@ -81,7 +81,7 @@ 
Utility Functions

     
 Computes the design effect (DEFF), which can subsequently be used to correct  sample size calculations using the 'sampszcalc' function.

 
     
sampszcalc

-    
 Performs sample size calculations, with optional correction for the design  effect deviating from ideal unity.

+    
 Performs sample size calculations, with optional correction for the design  effect deviating from unity.

 
   
Parameter functions

 
diff --git a/docs/index.html b/docs/index.html
index d3eb54dc..92811bff 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,7 +3,7 @@
 
   
   
-  
+  
   
   
   
diff --git a/docs/readme.html b/docs/readme.html
index 032c85f4..b1ff1ae1 100644
--- a/docs/readme.html
+++ b/docs/readme.html
@@ -90,8 +90,8 @@ 
Installation

 toolbox by double-clicking the ‘statistics-resampling.mltbx’ file in the
 matlab subdirectory. The toolbox installed in this way can be disabled
 or uninstalled via MATLAB’s Add-On manager. Currently, MEX files are
-included with the toolbox installation in Windows (32- or 64-bit), MacOS
-(Intel 64-bit) and Linux (64-bit). Without the MEX files, all
+included with the toolbox installation for Windows (32- or 64-bit),
+MacOS (Intel 64-bit) and Linux (64-bit). Without the MEX files, all
 functionality of the package is available, but some of the functions run
 slower.

 
Usage