SOCR Data Analysis Documentation - Revision history

Annie at 01:07, 22 January 2007

2007-01-22T01:07:46Z

Annie at 01:07, 22 January 2007

2007-01-22T01:07:39Z

Annie: /* More Examples */

2007-01-22T01:06:25Z

‎More Examples

Annie: /* More Examples */

2007-01-22T01:06:05Z

‎More Examples

Annie: /* More Examples */

2007-01-22T01:04:44Z

‎More Examples

Annie at 00:47, 22 January 2007

2007-01-22T00:47:23Z

IvoDinov at 05:45, 19 January 2007

2007-01-19T05:45:58Z

Annie at 21:54, 31 July 2006

2006-07-31T21:54:08Z

Annie at 21:42, 31 July 2006

2006-07-31T21:42:28Z

Annie at 21:36, 31 July 2006

2006-07-31T21:36:58Z

← Older revision		Revision as of 01:07, 22 January 2007
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	Under Survival Analysis:		Under Survival Analysis:
−	* Kaplan Meier Method	+	* Kaplan-Meier Method

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 * Two Independent Sample Wilconxon Test
 * Multiple Independent Sample Kruskal-Wallis Test
 === More Examples===

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 Survival Analysis using Kaplan-Meier
 * Example: [[Survival Analysis Using Kaplan-Meier]]
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 * Example: [[Multiple Independent Sample Kruskal Wallis Test]]
 Survival Analysis using Kaplan-Meier
 * Example: [[Survival Analysis Using Kaplan-Meier]]
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← Older revision		Revision as of 01:04, 22 January 2007
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	* Example: [[Multiple Independent Sample Kruskal Wallis Test]]		* Example: [[Multiple Independent Sample Kruskal Wallis Test]]
		+
		+	Survival Analysis using Kaplan-Meier
		+	* Example: [[Survival Analysis Using Kaplan-Meier]]
	{{translate\|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_Data_Analysis_Documentation}}		{{translate\|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_Data_Analysis_Documentation}}

← Older revision		Revision as of 05:45, 19 January 2007
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	* Example: [[Two Independent Sample Wilcoxon Test]]		* Example: [[Two Independent Sample Wilcoxon Test]]
		+
		+	{{translate\|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_Data_Analysis_Documentation}}

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 # Result Classes: under the directory of edu.ucla.stat.SOCR.analyses.result.
-Data class has a public, non-static method called "getAnalysis." This is the main and the only method you needed to implement the data analysis. It identifies the requested analysis model by taking a parameter, anaylisisType, from the caller. The legal analysis types are short primitaves defined in edu.ucla.stat.SOCR.analysis.model.AnalysisType.java. You must use those defined in this class in order for it to work. Then a model class is called by the Data class to do all the mathematical operations. All the computed results (e.g. parameter estimates and their standard error), will be put in Result class. The form of storage is by using Result's HashMap member variable (variable name is: texture). Just fetch this HashMap using "getTexture" method to get the results.
+A Data Object is the one that does the work for you. It stores the data you sibmit, as its member variables, and it calls Model classes (behind the scene) for results. It has "getter" methods that you can get computed results from. All the methods are public and non-static. See example below for how this works.
@@ Line 52: / Line 52: @@
 Here are a few things you should know when you code analysis method calls:
-* the Exception of the outer try above consists of: DataIsEmptyException (SOCR defined), WrongAnalysisException (SOCR defined), InstantiationException, IllegalAccessException, ClassNotFoundException. What if anaysis type is not specified corretly? A WrongAnalysisException would be generated. Or, what if the array that holds data is actually null or with length zero, a DataIsEmptyException will be generated. In a public method in Data, "Exception" is thrown and that include all the above. During any of the exception situation, check exception stacks for details.
+* The Exception of the outer try above consists of: DataIsEmptyException (SOCR defined), WrongAnalysisException (SOCR defined), InstantiationException, IllegalAccessException, ClassNotFoundException. What if anaysis type is not specified corretly? A WrongAnalysisException would be generated. Or, what if the array that holds data is actually null or with length zero, a DataIsEmptyException will be generated. In a public method in Data, "Exception" is thrown and that include all the above. During any of the exception situation, check exception stacks for details.
 * For the complete set of avaialble results, please see more examples below or check class API under edu.ucla.stat.SOCR.analsyses.example directory. All of the methods to fetch the output are under under edu.ucla.stat.SOCR.analsyses.result directory.
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 * A few words about addPreditor and addResponse methods: All the QUANTITATIVE varialbles must be submited in a form of int, long, float or double. All the FACTOR must be submitted in form of String. If the mapping of "QUANTITATIVE as double" and "FACTOR as String" is not used, an exception will be caused and the computation is paused. For example, if you intend to submit an array of data as QUANTITATIVE but you submit them as String, the code cannot compute for results.
 === Implemented Analysis Models===

@@ Line 18: / Line 18: @@
 <pre>
-double[] heightDoubleArray = new double[] {60, 55, 51, 54, 63};
+double[] height = new double[] {60, 55, 51, 54, 63};
-double[] weightDoubleArray = new double[] {190, 160, 110, 120, 130};
+double[] weight = new double[] {190, 160, 110, 120, 130};
-// you need to instantiate a data instance first.
+// First, you need to instantiate a data instance.
 Data testData = new Data();
-// then use the following line to get the result.
+// Second, submit the independent variable by addPredictor,
 try {
-	Result result = data.getAnalysis(AnalysisType.SIMPLE_LINEAR_REGRESSION);
+	SimpleLinearRegressionResult result = data.modelSimpleLinearRegression();
-	// Result.getTexture() returns a HashMap that holds some result data.
+	if (result != null) {
-	if (result != null) {
+		/* Getting the model's parameter estiamtes and statistics.
-		// is null if something in data goes wrong, e.g. exceptio. throwing.
+                Here are two of them: alpha(intercept) and beta(slope).
-		} catch (NullPointerException e) {
+		double alpha = result.getAlpha();
-			System.out.println("alpha could not be computed.");
+		double beta = result.getBeta();
-−
-		try {
+		System.out.println("alpha = " + alpha);
-			beta =
+		System.out.println("beta = " + beta );
+	}
 } catch (Exception e) {
-	System.out.println("Something is wrong. No result generated.");
+	System.out.println("Something is wrong. No result generated. " + e);
+}
 </pre>