popbio (version 2.7)

logi.hist.plot: Plot logistic regression

Description

Plot combined graphs for logistic regressions

Usage

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, ...)

Value

A logistic regression plot

Arguments

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

Author

M. de la Cruz Rot

References

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

Examples

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)