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69 lines
2.9 KiB
XML
Executable File
69 lines
2.9 KiB
XML
Executable File
<tool id="partialRsq" name="Compute partial R square" version="1.0.0">
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<description> </description>
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<command interpreter="python">
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partialR_square.py
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$input1
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$response_col
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$predictor_cols
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$out_file1
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1>/dev/null
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</command>
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<inputs>
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<param format="tabular" name="input1" type="data" label="Select data" help="Dataset missing? See TIP below."/>
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<param name="response_col" label="Response column (Y)" type="data_column" data_ref="input1" />
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<param name="predictor_cols" label="Predictor columns (X)" type="data_column" data_ref="input1" multiple="true">
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<validator type="no_options" message="Please select at least one column."/>
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</param>
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</inputs>
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<outputs>
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<data format="input" name="out_file1" metadata_source="input1" />
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</outputs>
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<requirements>
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<requirement type="python-module">rpy</requirement>
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</requirements>
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<tests>
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<!-- Test data with vlid values -->
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<test>
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<param name="input1" value="regr_inp.tabular"/>
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<param name="response_col" value="3"/>
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<param name="predictor_cols" value="1,2"/>
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<output name="out_file1" file="partialR_result.tabular"/>
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</test>
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</tests>
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<help>
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.. class:: infomark
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**TIP:** If your data is not TAB delimited, use *Edit Datasets->Convert characters*
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-----
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.. class:: infomark
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**What it does**
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This tool computes the Partial R squared for all possible variable subsets using the following formula:
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**Partial R squared = [SSE(without i: 1,2,...,p-1) - SSE (full: 1,2,..,i..,p-1) / SSE(without i: 1,2,...,p-1)]**, which denotes the case where the 'i'th predictor is dropped.
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In general, **Partial R squared = [SSE(without i: 1,2,...,p-1) - SSE (full: 1,2,..,i..,p-1) / SSE(without i: 1,2,...,p-1)]**, where,
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- SSE (full: 1,2,..,i..,p-1) = Sum of Squares left out by the full set of predictors SSE(X1, X2 … Xp)
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- SSE (full: 1,2,..,i..,p-1) = Sum of Squares left out by the set of predictors excluding; for example, if we omit the first predictor, it will be SSE(X2 … Xp).
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The 4 columns in the output are described below:
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- Column 1 (Model): denotes the variables present in the model
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- Column 2 (R-sq): denotes the R-squared value corresponding to the model in Column 1
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- Column 3 (Partial R squared_Terms): denotes the variable/s for which Partial R squared is computed. These are the variables that are absent in the reduced model in Column 1. A '-' in this column indicates that the model in Column 1 is the Full model.
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- Column 4 (Partial R squared): denotes the Partial R squared value corresponding to the variable/s in Column 3. A '-' in this column indicates that the model in Column 1 is the Full model.
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*R Development Core Team (2010). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.*
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</help>
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</tool>
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