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chore: Release 0.1.5-alpha.6 #SOCRFW-239
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32 changes: 18 additions & 14 deletions
32
app/partials/analysis/tools/machineLearning/kMeans/main.jade
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,16 +1,20 @@ | ||
| div(ng-controller="kMeansMainCtrl") | ||
| h2 2D k-means Clustering | ||
| p. | ||
| k-means clustering aims to partition n observations into k clusters in which each observation belongs | ||
| to the cluster with the nearest mean, serving as a prototype of the cluster. | ||
| div(ng-show="showresults").kmeans-results | ||
| p.lead <strong> Average accuracy: </strong> {{avgAccuracy}} | ||
| div.table-responsive | ||
| table.table.table-bordered.table-condensed | ||
| tr | ||
| th Label | ||
| th Accuracy | ||
| tr(ng-repeat="(label, acc) in accs") | ||
| td {{label}} | ||
| td {{acc.toFixed(2)}} | ||
| app-kmeans | ||
| div.lead.bg-danger(ng-hide="dataType == DATA_TYPES.FLAT") | ||
| | 2D k-means Clustering doesn't support current dataset. | ||
| | Only "flat" data tables are supported. | ||
| div(ng-hide="dataType != DATA_TYPES.FLAT") | ||
| p. | ||
| k-means clustering aims to partition n observations into k clusters in which each observation belongs | ||
| to the cluster with the nearest mean, serving as a prototype of the cluster. | ||
| div(ng-show="showresults").kmeans-results | ||
| p.lead <strong> Average accuracy: </strong> {{avgAccuracy}} | ||
| div.table-responsive | ||
| table.table.table-bordered.table-condensed | ||
| tr | ||
| th Label | ||
| th Accuracy | ||
| tr(ng-repeat="(label, acc) in accs") | ||
| td {{label}} | ||
| td {{acc.toFixed(2)}} | ||
| app-kmeans |
146 changes: 75 additions & 71 deletions
146
app/partials/analysis/tools/psychometrics/instrPerfEval/main.jade
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,73 +1,77 @@ | ||
| div(ng-controller="instrPerfEvalMainCtrl") | ||
| h2 Instrument Performance Evaluation | ||
| p. | ||
| Cronbach’s Alpha (α) is a measure of internal consistency or reliability of a psychometric instrument and measures | ||
| how well a set of items measure a single, one-dimensional latent aspect of individuals. | ||
| p.lead <strong> Cronbach's α: </strong> {{cronAlpha}} | ||
| div.table-responsive | ||
| table.table.table-bordered.table-striped | ||
| thead | ||
| tr | ||
| th Cronbach's alpha | ||
| th Internal consistency | ||
| tbody | ||
| tr.success | ||
| td <strong> α </strong> ≥ 0.9 | ||
| td Excellent (High-Stakes testing) | ||
| tr.success | ||
| td 0.7 ≤ <strong> α </strong> < 0.9 | ||
| td Good (Low-Stakes testing) | ||
| tr.info | ||
| td 0.6 ≤ <strong> α </strong> < 0.7 | ||
| td Acceptable | ||
| tr.warning | ||
| td 0.5 ≤ <strong> α </strong> < 0.6 | ||
| td Poor | ||
| tr.danger | ||
| td <strong> α </strong> < 0.5 | ||
| td Unacceptable | ||
| p. | ||
| Cronbach's α coefficient is a point estimate of the reliability. | ||
| Its standard error is important to construct an interval estimation of its true value | ||
| and to obtain statistical inference about its significance. | ||
| There are parametric and non-parametric methods to estimate the variance of Cronbach's α, | ||
| and compute confidence intervals. | ||
| p <strong> Cronbach’s Alpha confidence intervals </strong> | ||
| p.bg-info ID confidence interval: {{cronAlphaIdInterval}} | ||
| p.bg-info Koning and Franses confidence interval: {{cronAlphaKfInterval}} | ||
| p.bg-info Bootstrap confidence interval: {{cronAlphaBootstrapInterval}} | ||
| p.bg-info Logit confidence interval: {{cronAlphaLogitInterval}} | ||
| p.bg-info Asymptotically distribution-free (ADF) interval: {{cronAlphaAdfInterval}} | ||
| br | ||
| p <strong> Other metrics of reliability: </strong> | ||
| p. | ||
| The Intra-class correlation coefficient (ICC) assesses the consistency, or reproducibility, | ||
| of quantitative measurements made by different observers measuring the same quantity. | ||
| Broadly speaking, the ICC is defined as the ratio of between-cluster variance to total variance. | ||
| p.bg-info Intraclass correlation coefficient (ICC): {{icc}} | ||
| p. | ||
| In Split-Half Reliability assessment, the test is split in half (e.g., odd / even) creating "equivalent forms". | ||
| The two "forms" are correlated with each other and the correlation coefficient is adjusted | ||
| to reflect the entire test length, using the Spearman-Brown Prophecy formula. | ||
| p.bg-info Split-Half Reliability coefficient: {{splitHalfCoef}} | ||
| p. | ||
| The Kuder–Richardson Formula 20 (KR-20) is a very reliable internal reliability estimate which simulates | ||
| calculating split-half reliability for every possible combination of items. | ||
| The Cronbach's α and KR-20 are similar ― KR-20 is a derivative of the Cronbach's α with the advantage that | ||
| it can handle both dichotomous and continuous variables, however, KR-20 can't be used | ||
| when multiple-choice questions involve partial credit and require systematic item-based analysis. | ||
| p.bg-info Kuder–Richardson Formula 20 (KR-20): {{kr20}} | ||
| br | ||
| p | ||
| small | ||
| p <strong> References: </strong> | ||
| p 1. | ||
| a(href='http://wiki.socr.umich.edu/index.php/SMHS_Cronbachs'). | ||
| Scientific Methods for Health Sciences - Instrument Performance Evaluation: Cronbach's α | ||
| p. | ||
| 2. TSAGRIS, MICHAIL, CONSTANTINOS C. FRANGOS, and CHRISTOS C. FRANGOS. | ||
| "Confidence intervals for Cronbach’s reliability coefficient." | ||
| p. | ||
| 3. Maydeu-Olivares, Alberto, Donna L. Coffman, and Wolfgang M. Hartmann. | ||
| "Asymptotically distribution-free (ADF) interval estimation of coefficient alpha." | ||
| Psychological methods 12.2 (2007): 157. | ||
| div.lead.bg-danger(ng-hide="dataType == DATA_TYPES.FLAT") | ||
| | Instrument Performance Evaluation doesn't support current dataset. | ||
| | Only "flat" data tables are supported. | ||
| div(ng-hide="dataType != DATA_TYPES.FLAT") | ||
| p. | ||
| Cronbach’s Alpha (α) is a measure of internal consistency or reliability of a psychometric instrument and measures | ||
| how well a set of items measure a single, one-dimensional latent aspect of individuals. | ||
| p.lead <strong> Cronbach's α: </strong> {{cronAlpha}} | ||
| div.table-responsive | ||
| table.table.table-bordered.table-striped | ||
| thead | ||
| tr | ||
| th Cronbach's alpha | ||
| th Internal consistency | ||
| tbody | ||
| tr.success | ||
| td <strong> α </strong> ≥ 0.9 | ||
| td Excellent (High-Stakes testing) | ||
| tr.success | ||
| td 0.7 ≤ <strong> α </strong> < 0.9 | ||
| td Good (Low-Stakes testing) | ||
| tr.info | ||
| td 0.6 ≤ <strong> α </strong> < 0.7 | ||
| td Acceptable | ||
| tr.warning | ||
| td 0.5 ≤ <strong> α </strong> < 0.6 | ||
| td Poor | ||
| tr.danger | ||
| td <strong> α </strong> < 0.5 | ||
| td Unacceptable | ||
| p. | ||
| Cronbach's α coefficient is a point estimate of the reliability. | ||
| Its standard error is important to construct an interval estimation of its true value | ||
| and to obtain statistical inference about its significance. | ||
| There are parametric and non-parametric methods to estimate the variance of Cronbach's α, | ||
| and compute confidence intervals. | ||
| p <strong> Cronbach’s Alpha confidence intervals </strong> | ||
| p.bg-info ID confidence interval: {{cronAlphaIdInterval}} | ||
| p.bg-info Koning and Franses confidence interval: {{cronAlphaKfInterval}} | ||
| p.bg-info Bootstrap confidence interval: {{cronAlphaBootstrapInterval}} | ||
| p.bg-info Logit confidence interval: {{cronAlphaLogitInterval}} | ||
| p.bg-info Asymptotically distribution-free (ADF) interval: {{cronAlphaAdfInterval}} | ||
| br | ||
| p <strong> Other metrics of reliability: </strong> | ||
| p. | ||
| The Intra-class correlation coefficient (ICC) assesses the consistency, or reproducibility, | ||
| of quantitative measurements made by different observers measuring the same quantity. | ||
| Broadly speaking, the ICC is defined as the ratio of between-cluster variance to total variance. | ||
| p.bg-info Intraclass correlation coefficient (ICC): {{icc}} | ||
| p. | ||
| In Split-Half Reliability assessment, the test is split in half (e.g., odd / even) creating "equivalent forms". | ||
| The two "forms" are correlated with each other and the correlation coefficient is adjusted | ||
| to reflect the entire test length, using the Spearman-Brown Prophecy formula. | ||
| p.bg-info Split-Half Reliability coefficient: {{splitHalfCoef}} | ||
| p. | ||
| The Kuder–Richardson Formula 20 (KR-20) is a very reliable internal reliability estimate which simulates | ||
| calculating split-half reliability for every possible combination of items. | ||
| The Cronbach's α and KR-20 are similar ― KR-20 is a derivative of the Cronbach's α with the advantage that | ||
| it can handle both dichotomous and continuous variables, however, KR-20 can't be used | ||
| when multiple-choice questions involve partial credit and require systematic item-based analysis. | ||
| p.bg-info Kuder–Richardson Formula 20 (KR-20): {{kr20}} | ||
| br | ||
| p | ||
| small | ||
| p <strong> References: </strong> | ||
| p 1. | ||
| a(href='http://wiki.socr.umich.edu/index.php/SMHS_Cronbachs'). | ||
| Scientific Methods for Health Sciences - Instrument Performance Evaluation: Cronbach's α | ||
| p. | ||
| 2. TSAGRIS, MICHAIL, CONSTANTINOS C. FRANGOS, and CHRISTOS C. FRANGOS. | ||
| "Confidence intervals for Cronbach’s reliability coefficient." | ||
| p. | ||
| 3. Maydeu-Olivares, Alberto, Donna L. Coffman, and Wolfgang M. Hartmann. | ||
| "Asymptotically distribution-free (ADF) interval estimation of coefficient alpha." | ||
| Psychological methods 12.2 (2007): 157. |
2 changes: 1 addition & 1 deletion
2
app/partials/analysis/tools/psychometrics/instrPerfEval/sidebar.jade
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,10 +1,14 @@ | ||
| #dt_example(style='height: 400px') | ||
| .ui-layout-north#wranglerNorthPanel | ||
| #wranglerDashboard | ||
| .ui-layout-west#profilerWestPanel | ||
| #transformEditor.transformEditor | ||
| .ui-layout-center#profilerCenterPanel | ||
| #table | ||
| #preview | ||
| .spacer | ||
| .ui-layout-south | ||
| div | ||
| div.lead.bg-danger(ng-hide="dataType == DATA_TYPES.FLAT") | ||
| | Data Wrangler doesn't support current dataset. | ||
| | Only "flat" data tables are supported. | ||
| #dt_example(style='height: 400px', ng-hide="dataType != DATA_TYPES.FLAT", ng-cloak) | ||
| .ui-layout-north#wranglerNorthPanel | ||
| #wranglerDashboard | ||
| .ui-layout-west#profilerWestPanel | ||
| #transformEditor.transformEditor | ||
| .ui-layout-center#profilerCenterPanel | ||
| #table | ||
| #preview | ||
| .spacer | ||
| .ui-layout-south |
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