logi.hist.plot: Plot logistic regression
In popbio: Construction and Analysis of Matrix Population Models

Description Usage Arguments Value Author(s) References Examples

Plot combined graphs for logistic regressions

logi.hist.plot(independ, depend, logi.mod = 1, type = "dit",
  boxp = TRUE, rug = FALSE, ylabel = "Probability",
  ylabel2 = "Frequency", xlabel = "", mainlabel = "", las.h = 1,
  counts = FALSE, ...)

`independ`	explanatory variable
`depend`	dependent variable, typically a logical vector
`logi.mod`	type of fitting, 1 = logistic; 2 = "gaussian" logistic
`type`	type of representation, "dit" = dit plot; "hist" = histogram
`boxp`	TRUE = with box plots, FALSE = without
`rug`	TRUE = with rug plots, FALSE = without
`ylabel`	y-axis label
`ylabel2`	2nd y-axis label
`xlabel`	x-axix label
`mainlabel`	overall title for plot
`las.h`	orientation of axes labels (0 = vertical, 1 = horizontal
`counts`	add counts above histogram bars
`...`	additional options passed to logi.hist

A logistic regression plot

M. de la Cruz Rot

de la Cruz Rot, M. 2005. Improving the Presentation of Results of Logistic Regression with R. ESA Bulletin 86:41-48. http://esapubs.org/bulletin/backissues/086-1/bulletinjan2005.htm

aq.trans$survived <- aq.trans$fate!="dead"
a <- subset(aq.trans, leaf<50 & stage!="recruit", c(leaf,survived))
logi.hist.plot(a$leaf,  a$survived,
  type="hist", boxp=FALSE, counts=TRUE, int=10,
  ylabel="Survival probability", ylabel2="Number of plants",
  xlab="Number of leaves")
b <- glm(survived ~ leaf, binomial, data=a)
summary(b)