SOCR Analyses Expansion

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(Adding a Hierarchical Clustering and Classification Analysis)
 
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===Project specs===
===Project specs===
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* All code must be pure Java, compatible with Java 1.4, and integrates with [http://code.google.com/p/socr/source/browse/#svn%2Ftrunk%2FSOCR2.6 entire SOCR code].
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* All code must be pure Java, compatible with Java 1.5, and integrates with [http://code.google.com/p/socr/source/browse/#svn%2Ftrunk%2FSOCR2.6 entire SOCR code].
* [[SOCR_EduMaterials_AnalysesCommandLine|try to also provide a command-line invocation of the new SOCR Analysis applet]], see the [http://code.google.com/p/socr/source/browse/#svn%2Ftrunk%2FSOCR2.6%2Fsrc%2Fedu%2Fucla%2Fstat%2FSOCR%2Fanalyses%2Fcommand examples of SOCR command-line source-code]. The command-line interface is useful for pipelining SOCR analysis tools as part of various [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3111084/ heterogeneous graphical workflow environments].
* [[SOCR_EduMaterials_AnalysesCommandLine|try to also provide a command-line invocation of the new SOCR Analysis applet]], see the [http://code.google.com/p/socr/source/browse/#svn%2Ftrunk%2FSOCR2.6%2Fsrc%2Fedu%2Fucla%2Fstat%2FSOCR%2Fanalyses%2Fcommand examples of SOCR command-line source-code]. The command-line interface is useful for pipelining SOCR analysis tools as part of various [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3111084/ heterogeneous graphical workflow environments].
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** [http://factominer.free.fr/docs/HCPC_husson_josse.pdf See this use-case for usage and validation of Java implementation (PDF)]
** [http://factominer.free.fr/docs/HCPC_husson_josse.pdf See this use-case for usage and validation of Java implementation (PDF)]
** Test data: [[SOCR_Data_NIPS_InfantVitK_ShotData|SOCR Neonate Infant Pain Score (NIPS) Data (Vitamin K shots)]]
** Test data: [[SOCR_Data_NIPS_InfantVitK_ShotData|SOCR Neonate Infant Pain Score (NIPS) Data (Vitamin K shots)]]
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====Adding the Skillings-Mack (SM) Analysis of Treatment Effects for Unbalanced Designs====
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The *Skillings-Mack* (SM) test-statistics provides a general method for comparing treatments for incomplete blocks when the observations may be randomly missing and the number of observations per cell are different. The SM) test-statistics generalized the [[SOCR_EduMaterials_AnalysisActivities_Friedman|Friedman test]] when there are missing data or there are different number of observations per cell. The resources below provide details and examples of how to compute the SM statistics and apply it to analyze real data.
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* [http://support.sas.com/resources/papers/proceedings10/275-2010.pdf Calculation of the Skillings-Mack statistic] based on [http://pyramid.kmutnb.ac.th/TOC_BOOK/B14667125.pdf (Hollander and Wolfe, 1999)]
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* [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2761045/ The Skillings–Mack test]
=== Command-line SOCR analysis interface===
=== Command-line SOCR analysis interface===

Current revision as of 20:05, 10 January 2013

Contents

SOCR Project - SOCR Analyses Expansion Project

Project Goal

To expand, and redesign as necessary, the current collection of SOCR Analyses Tools. This may involve implementing new SOCR analyses applets, redesigning the analyses as HTML5/JavaScript, refactoring and improving the organization of the SOCR Analyses package, extend the command-line SOCR analysis interface, etc.

Background

Explore and research the SOCR Analyses first. The Analyses package is one of the major SOCR packages and consists of a collection of applets that enables the statistical modeling, analysis and inference on user provided data. It currently has parametric and non-parametric, linear and non-linear, quantitative and qualitative, univariate and multivariate types of analyses.

Project specs

Adding new SOCR Analyses

To expand the framework of SOCR analyses, first review the following resources:

Adding a Hierarchical Clustering and Classification Analysis

Consider adding a new SOCR Hierarchical Data Clustering and Classification analysis applet. Below are some useful resources:

Adding the Skillings-Mack (SM) Analysis of Treatment Effects for Unbalanced Designs

The *Skillings-Mack* (SM) test-statistics provides a general method for comparing treatments for incomplete blocks when the observations may be randomly missing and the number of observations per cell are different. The SM) test-statistics generalized the Friedman test when there are missing data or there are different number of observations per cell. The resources below provide details and examples of how to compute the SM statistics and apply it to analyze real data.

Command-line SOCR analysis interface

To extend the command-line SOCR analysis interface, see the following resources:

References

The following references would be useful for this project:


Available_SOCR_Development_Projects

SOCR_ProposalSubmissionGuidelines




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