> On Jul 30, 2017, at 11:28 AM, Kristi Glover <kristi.glover at
hotmail.com> wrote:
>
> Hi R Users,
>
> I created interaction plots in ggplot2 and was trying to add output of two
way ANOVA models, especially only interaction ( example treatment*control
F(XX, XX) = xxx, p = xxx) into figures, but i was not able to add. Would you
mind to help on how I can add information into each figure? I have attached the
example data and the code that I used for this.
>
>
> dat<-structure(list(Sites = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Site1", "Site2"),
class = "factor"),
>
> Period = structure(c(2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L,
>
> 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L,
>
> 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L,
>
> 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L,
>
> 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L,
>
> 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L,
>
> 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
>
> 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L,
>
> 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L,
>
> 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L,
>
> 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L,
>
> 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L,
>
> 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L,
>
> 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L,
>
> 1L, 1L, 1L), .Label = c("After", "Before"), class =
"factor"),
>
> Group = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L), .Label = c("Control", "Treatment"), class =
"factor"),
>
> Env1 = c(-23.99, 0, -23.4, -24.77, 4.92, 4.94, 4.96, 4.93,
>
> 4.97, 4.99, 5.06, -12.12, 5.2, 0, 0, 5.07, 5.09, 0, 5.07,
>
> 0, 5, 0, -27.63, 4.44, 0, 0, 0, 4.33, 4.33, 0, 5.07, 5.07,
>
> 5.03, 5.01, 0, 0, 4.97, 0, 4.98, 5.07, 0, 5.08, 0, 0, 4.91,
>
> -35.98, 0, 0, 0, 5.2, 0, 4.89, 5.07, 0, 4.96, 4.86, 4.96,
>
> 0, 4.95, 5.07, 0, 0, -34.07, 5.06, 4.98, 4.94, 0, 4.95, 5.07,
>
> 0, 0, 0, -38.32, -31.91, -29.75, 0, 0, 4.69, 4.48, 0, 0,
>
> 4.57, 4.78, 0, 0, 4.74, 5.02, 4.87, 0, 0, 0, 4.65, -52.2,
>
> 0, -32.11, 5.05, 0, 5.03, 5.13, 0, 0, 0, -33.75, 4.84, 4.74,
>
> 0, 4.82, -32.98, 5.04, 0, 0, 4.95, 5.18, 5.18, 0, 0, 4.57,
>
> 4.84, 4.74, 0, 4.78, 0, 4.78, 4.36, 4.45, 3.68, 0, 4.16,
>
> 4.61, 0, 4.63, 0, 0, -28.65, 4.96, 4.42, 0, 0, 0, 0, 0, 4.89,
>
> 4.96, 4.93, 0, 0, 4.96, 0, 0, 0, 0, 4.42, 0, 0, 0, 4.82,
>
> 0, 0, 0, -34.71, 0, 4.59, 0, 4.86, 0, 0, 4.75, 0, 0, 4.65,
>
> 4.8, 0, 0, 4.87, 4.86, 0, 0, 0, 4.83, 0, 4.85, 0, 4.48, 4.38,
>
> 0, 0, 4.53, 0, 4.79, 0, 0, 0, 4.7, 0, 4.84, 0, 0, 0, 4.35,
>
> 4.72, 4.72, 4.65, 4.65, 4.39, 4.73, 4.62, 0, 4.76, 0, 5,
>
> 0, 4.86, 0, -13.38, 0, 4.73, 0, 0, 0, 4.58, 4.76, 0, 0, 0,
>
> 0, 4.68, 4.74, 0, 0, 0, 4.83, 0, 0, 0, 0, 0, 0), Env2 = c(-5.89,
>
> 0, -4.13, -8.88, 2.79, -0.31, -1.21, -3.72, -0.52, -6.52,
>
> -10.28, -0.27, -21.27, 0, 0, -5.62, -11.49, 0, -4.85, 0,
>
> -0.8, 0, -5.4, 0.63, 0, 0, 0, -10.92, -9.41, 0, -9.62, -9.15,
>
> -4.32, -5.63, 0, 0, -6.07, 0, -3.34, -11.85, 0, -10.36, 0,
>
> 0, -5.29, 3, 0, 0, 0, -16.94, 0, 1.47, -8.51, 0, -3.07, -3.51,
>
> -4.79, 0, -2.11, -20.19, 0, 0, -9.91, -16.85, -1.4, -3.96,
>
> 0, -3.83, -7.14, 0, 0, 0, -1.58, -2.42, -1.56, 0, 0, 4.45,
>
> 23.76, 0, 0, 15.1, 5.86, 0, 0, 8.26, -9.56, 6.43, 0, 0, 0,
>
> -1.93, 7.2, 0, 0.39, -6.75, 0, -4.4, -9.39, 0, 0, 0, 2.41,
>
> 3.23, 2.71, 0, -1, -3.54, -7.19, 0, 0, -5.68, -13.39, -15.14,
>
> 0, 0, 0.8, 7.74, 5.58, 0, -7.4, 0, 2.63, 10.5, 8.66, 4.49,
>
> 0, 4.87, 16.63, 0, 9.14, 0, 0, 24.56, -8.22, 5.91, 0, 0,
>
> 0, 0, 0, -8.03, -7.54, -1.83, 0, 0, 0.67, 0, 0, 0, 0, 7.6,
>
> 0, 0, 0, -4.54, 0, 0, 0, -5.3, 0, 3.09, 0, 1.35, 0, 0, 12.39,
>
> 0, 0, 3.66, 5.77, 0, 0, 6, 3.98, 0, 0, 0, -2, 0, 0.99, 0,
>
> 10.58, 7.31, 0, 0, 5.32, 0, 9.73, 0, 0, 0, 7.23, 0, 8.53,
>
> 0, 0, 0, 22.69, 0.22, 8.5, 15.74, 13.91, 17.44, 14.93, 13.69,
>
> 0, -6.28, 0, -5.07, 0, -2.03, 0, 3.01, 0, 11.02, 0, 0, 0,
>
> 16.53, 7.34, 0, 0, 0, 0, -8.31, 3.31, 0, 0, 0, -2.33, 0,
>
> 0, 0, 0, 0, 0)), .Names = c("Sites", "Period",
"Group", "Env1",
>
> "Env2"), class = "data.frame", row.names = c(NA,
-237L))
>
>
> long<-melt(dat, id=c('Sites', 'Period',
'Group'))
>
> head(long)
>
> df<-ddply(long, c("Period",
"Group","variable"), summarise,
>
> N = length(value),
>
> mean = mean(value, na.rm=TRUE),
>
> sd = sd(value, na.rm=TRUE),
>
> se = sd / sqrt(N))
>
> df$Period1 <- factor(df$Period, levels=c("Before",
"After"))
>
> gp <- ggplot(df, aes(x=Period1, y=mean, colour=Group, group=Group))
>
> gp<-gp + geom_line(aes(linetype=Group), size=.6) +
>
> geom_point(aes(shape=Group), size=3) +
>
> geom_errorbar(aes(ymax=mean+se, ymin=mean-se), width=.1)
>
> gp+facet_grid(.~variable)
>
>
> ###two way anova interactions analysis
>
> # since I do have
>
> long$newFactor<-paste(long$Sites,long$variable)
>
> models <- dlply(long, "newFactor", function(df)
>
> lm(value ~ Group*Period, data = long))
>
> summary(models)
All of those items in the `models`-object are the same.
What part of these models do you propose to add to the plot?
models[[1]]
Call:
lm(formula = value ~ Group * Period, data = long)
Coefficients:
(Intercept) GroupTreatment
0.2130 -1.2245
PeriodBefore GroupTreatment:PeriodBefore
-0.4174 2.4311
>
> But I could not add the information of the interaction (F and its P
values) in each above figures. Would you mind to hep me. It will be highly
appreciated.
summary(models[[1]])
Call:
lm(formula = value ~ Group * Period, data = long)
Residuals:
Min 1Q Median 3Q Max
-51.996 -1.002 0.204 4.429 24.347
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.2130 0.6581 0.324 0.746
GroupTreatment -1.2245 1.1627 -1.053 0.293
PeriodBefore -0.4174 0.8654 -0.482 0.630
GroupTreatment:PeriodBefore 2.4311 1.5701 1.548 0.122
Residual standard error: 7.787 on 470 degrees of freedom
Multiple R-squared: 0.005522, Adjusted R-squared: -0.0008256
F-statistic: 0.8699 on 3 and 470 DF, p-value: 0.4565
> Thanks
>
>
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It didn't make a difference in this posting but you should learn to post in
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--
David Winsemius
Alameda, CA, USA
'Any technology distinguishable from magic is insufficiently advanced.'
-Gehm's Corollary to Clarke's Third Law