REGIONS_OF_SIGNIFICANCE {SIMPLE.REGRESSION} | R Documentation |
Plots of Johnson-Neyman regions of significance for interactions
Description
Plots of Johnson-Neyman regions of significance for interactions in moderated multiple regression, for both MODERATED_REGRESSION models (which are produced by this package) and for lme models (from the nlme package).
Usage
REGIONS_OF_SIGNIFICANCE(model,
IV_range=NULL, MOD_range=NULL,
plot_title=NULL, Xaxis_label=NULL,
Yaxis_label=NULL, legend_label=NULL,
names_IV_MOD=NULL)
Arguments
model |
The name of a MODERATED_REGRESSION model, or of an lme model from the nlme package. |
IV_range |
(optional) The range of the IV to be used in the plot.
|
MOD_range |
(optional) The range of the MOD values to be used in the plot.
|
plot_title |
(optional) The plot title.
|
Xaxis_label |
(optional) A label for the X axis to be used in the plot.
|
Yaxis_label |
(optional) A label for the Y axis to be used in the plot.
|
legend_label |
(optional) The legend label.
|
names_IV_MOD |
(optional) and for lme/nlme models only. Use this argument to ensure that the IV and MOD variables are correctly identified for the plot. There are three scenarios in particular that may require specification of this argument:
Example: names_IV_MOD = c('IV name', 'MOD name') |
Value
A list with the following possible components:
JN.data |
The Johnson-Neyman results for a moderated regression. |
ros |
The Johnson-Neyman regions of significance for a moderated regression. |
Author(s)
Brian P. O'Connor
References
Bauer, D. J., & Curran, P. J. (2005). Probing interactions in fixed and multilevel
regression: Inferential and graphical techniques. Multivariate Behavioral
Research, 40(3), 373-400.
Huitema, B. (2011). The analysis of covariance and alternatives: Statistical
methods for experiments, quasi-experiments, and single-case studies. John Wiley & Sons.
Johnson, P. O., & Neyman, J. (1936). Tests of certain linear hypotheses and their
application to some educational problems. Statistical Research Memoirs, 1, 57-93.
Johnson, P. O., & Fey, L. C. (1950). The Johnson-Neyman technique, its theory, and
application. Psychometrika, 15, 349-367.
Pedhazur, E. J. (1997). Multiple regression in behavioral research: Explanation
and prediction. (3rd ed.). Wadsworth Thomson Learning
Rast, P., Rush, J., Piccinin, A. M., & Hofer, S. M. (2014). The identification of regions of
significance in the effect of multimorbidity on depressive symptoms using longitudinal data: An
application of the Johnson-Neyman technique. Gerontology, 60, 274-281.
Examples
head(data_Cohen_Aiken_West_2003_7)
CAW_7 <-
MODERATED_REGRESSION(data=data_Cohen_Aiken_West_2003_7, DV='yendu',
IV='xage',IV_range='tumble',
MOD='zexer', MOD_levels='quantiles',
quantiles_IV=c(.1, .9), quantiles_MOD=c(.25, .5, .75),
plot_type = 'interaction')
REGIONS_OF_SIGNIFICANCE(model=CAW_7)
head(data_Bauer_Curran_2005)
HSBmod <-nlme::lme(MathAch ~ Sector + CSES + CSES:Sector,
data = data_Bauer_Curran_2005,
random = ~1 + CSES|School, method = "ML")
summary(HSBmod)
REGIONS_OF_SIGNIFICANCE(model=HSBmod,
plot_title='Johnson-Neyman Regions of Significance',
Xaxis_label='Child SES',
Yaxis_label='Slopes of School Sector on Math achievement')
# moderated regression -- with numeric values for IV_range & MOD_levels='AikenWest'
mharsh_agg <-
MODERATED_REGRESSION(data=data_OConnor_Dvorak_2001, DV='Aggressive_Behavior',
IV='Maternal_Harshness', IV_range=c(1,7.7),
MOD='Resiliency', MOD_levels='AikenWest',
quantiles_IV=c(.1, .9), quantiles_MOD=c(.25, .5, .75),
center = FALSE,
plot_type = 'interaction',
DV_range = c(1,6),
Xaxis_label='Maternal Harshness',
Yaxis_label='Adolescent Aggressive Behavior',
legend_label='Resiliency')
REGIONS_OF_SIGNIFICANCE(model=mharsh_agg,
plot_title='Johnson-Neyman Regions of Significance',
Xaxis_label='Resiliency',
Yaxis_label='Slopes of Maternal Harshness on Aggressive Behavior')