Assumptions Underlying
the PPMCC: PPMCC is appropriate
when three conditions exists: underlying
measurement scales for the variables being correlated must be interval or ratio level, Scores for each variable should be normally distributed (no
skewness should be there), relationship between the two
variables should be fundamentally linear.
1.
The underlying measurement scales for the variables
being correlated must be interval or ratio
level (i.e., they are continuous).
Examples
of variables that meet this criterion include revision time (measured in
hours), intelligence (measured using IQ score), exam performance (measured from
0 to 100), weight (measured in kg), and so forth.
2.
Bivariate
Normality (Bivariate normal distribution): Scores for each variable
should be normally
distributed. No skewness, neither positive nor negative should be
there.
3.
Relationship between the two variables should
be fundamentally linear.
4.
There should be no
significant outliers (single data points within the data that do not
follow the usual pattern).
5.
Homoscedasticity: It means variance around
regression line should be same for all values of predictor variable (X). A
relation is called heteroscedastic when all the points very (bunched up) near
the regression line. Homoscedasticity is
violated when there is much more variability (points are scattered away
from the regression line) around the regression line.
Serious violations in
homoscedasticity (assuming a distribution of data is homoscedastic when in
actuality it is heteroscedastic) result in underemphasizing
the Pearson coefficient. Assuming homoscedasticity assumes that
variance is fixed throughout a distribution.
Heteroscedasticity is
caused by non-normality of one of the variables, an indirect relationship
between variables, or to the effect of a data transformation.
Heteroscedasticity is not fatal to an analysis, the analysis is weakened, not
invalidated. Homoscedasticity is detected with scatterplots and is
rectified through transformation.
These notes are written by S C Joshi during EPSY 635 Course, Fall 2015, Texas A&M University. Acknowledgements to Dr. Bob Hall, Professor, EPSY, Texas A&M University for his assistance in understanding these terms during the course
No comments:
Post a Comment