Changes between Version 2 and Version 3 of SOPs/anova

Timestamp:

05/24/13 11:55:46 (12 years ago)

Author:

gbell

Comment:

--

SOPs/anova

@@ -2 +2 @@
 
 See the [http://www.graphpad.com/support/faqid/1745/ Prism help page] for some general considerations.
+
+Note that ANOVA and post-hoc tests can be performed in Prism too.
+
 
 ==== Reading in Data ====
@@ -7 +10 @@
 
   * Use read.* or create appropriate dataframe
-
 
 {{{
@@ -58 +60 @@
 }}}
 
-== One-way ANOVA ==
+== Repeated-measures ANOVA ==
+
+Repeated-measures ANOVA is typically needed if multiple measurements are made on the same sample (such as assaying a mouse's weight during a time course).
+
+== Two-way ANOVA ==
+
+Two-way ANOVA should be used for experiments where to different factors are being varied (such as comparing different treatments of different genotypes of mice).
+
+==== Reading in Data ====
 
 
+  * Use read.* or create appropriate dataframe
+
+{{{
+# Input data from a tab-delimited text file of the format
+# weight treatment genotype
+# 56   a   ko
+# 29   b   wt
+# 60   a   wt
+# ...
+strains = read.delim("brain_weights.txt",header=TRUE)
+}}}
+
+==== Creating an ANOVA Table ====
+  * Use the command //anova// or //aov// with summary.  The first argument is the dependent variable, followed by ~, and then by independent variable(s).
+  * So if we want to set up a model where weight is a function of the group (e.g., the weight potentially depends on the group)
+
+{{{
+# Syntax 1
+anova( lm(weight ~ group * genotype, data=strains) )
+anova( lm(weight ~ genotype * group, data=strains) )
+
+# Syntax 2
+summary( aov(weight ~ group * genotype, data=strains) )
+summary( aov(weight ~ genotype * group, data=strains) )
+}}}
+
+== Post-Test: Comparing All Pairs of Means ==