Changes between Initial Version and Version 1 of SOPs/anova

Timestamp:

01/23/13 16:49:43 (13 years ago)

Author:

trac

Comment:

--

SOPs/anova

@@ +1 @@
+== One-way ANOVA ==
+
+See the [http://www.graphpad.com/support/faqid/1745/ Prism help page] for some general considerations.
+
+==== Reading in Data ====
+
+
+  * Use read.* or create appropriate dataframe
+
+
+{{{
+  #Eg. testing 4 different strains by creating a dataframe
+  PA7<-c(56,60,44,53)
+  PA7_dGra15<-c(29,38,18,35)
+  PA7_Rop16l<-c(11,25,7,18)
+  PA7_Rop16l_dGra15<-c(26,44,20,32)
+  strains<-data.frame(PA7, PA7_dGra15, PA7_Rop16l, PA7_Rop16l_dGra15)
+  strains_stack<-stack(strains)
+  
+  #Eg. from Mathias' Stats Lecture
+  brainweight <- read.csv("brain_weights.csv",header=TRUE)
+
+}}}
+  
+==== Creating an ANOVA Table ====
+  * Use the command //anova// or //aov// with summary.  The first arg is the dependent var, followed by ~, and then by independent variable(s)
+
+ 
+{{{
+ #column headers were not given above, default are "values" and "ind"
+  anova(lm(values~ind, data=strains_stack))
+  #or save to file
+  x<-anova(lm(values~ind, data=strains_stack))
+  write.table(x, file="strains1_anova.txt", quote=F)
+  
+  #Eg. from Mathias' Stats Lecture
+  summary(aov(Weight~Group))
+
+}}}
+
+== Post-Test: Comparing All Pairs of Means ==
+
+==== Tukey ====
+    * "Tukey's method is more conservative but may miss real differences too often" - Intuitive Biostatistics (p.259)
+
+
+{{{
+  TukeyHSD(aov(values~ind, data=strains_stack))
+  
+  #Eg. from Mathias' Stats Lecture
+  TukeyHSD(aov(brainweight$Weight~brainweight$Group))
+  
+
+}}}
+
+==== Dunnett ====
+  * Useful if you want to compare a reference group to all other groups (instead of doing an all vs. all comparison) 
+  * The first group is used as the reference group, so name your groups so this is the case.
+
+
+{{{
+  library(multcomp)
+  summary(glht(lm(Weight ~ Group, data=brainweight), linfct=mcp(Group="Dunnett")))
+
+}}}