Description Usage Arguments Details Value Author(s) References Examples
Johnson-Neyman Technique
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dat1 |
|
dat2 |
|
which.is.fact |
Currently not implemented |
alpha |
Desired alpha level for comparison |
total.comp |
Total number of comparisons |
use_sma |
Boolean; use standardized major axis regression |
silent |
Suppress messages |
This function performs the Johnson-Neyman Technique on data
contained in two data.frame
s. Currently only the method for
data.frame
s is implemented.
A list of type jnt
containing:
dat1 |
Data set 1 |
dat2 |
Data set 2 |
alpha |
Alpha level |
slope1 |
Slope for data set 1 |
int1 |
intercept for data set 1 |
slope2 |
Slope for data set 2 |
int2 |
intercept for data set 2 |
lower |
Lower edge of range of no significant different in slopes |
upper |
Upper edge of range of no significant different in slopes |
Kevin Middleton (middletonk@missouri.edu)
Johnson PO and Neyman J (1936) Tests of certain linear hypotheses and their application to some educational problems. Statistical Research Memoirs 1: 57-93.
Hunka S and Leighton J (1997) Defining Johnson-Neyman regions of significance in three-covariate ANCOVA using Mathematica. Journal of Educational and Behavioral Statistics 22: 361-387.
White CR (2003) Allometric analysis beyond heterogenous regression slopes: Use of the Johnson-Neyman Technique in comparative biology. Physiol Biochem Zool 76: 135-140.
Examples:
White CR (2003) The influence of foraging mode and arid adaptation on the basal metabolic rates of burrowing mammals. Physiol Biochem Zool 76: 122-134.
Lavin SR, Karasov WH, Ives AR, Middleton KM, Garland T (2008) Morphometrics of the avian small intestine compared with that of nonflying mammals: A phylogenetic approach. Physiol Biochem Zool 81: 526-550.
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