146008
Research Design Decision Tree
- How Many
Variables?
- 1 VARIABLE
- Scale of Measurement?
- Nominal
- Info about Distribution?
- Central Tendency:
tables for modal value
- Distribution: tables for frequency
of modal value or class
- Frequencies: tables for
relative and absolute
- Central Tendency:
tables for modal value
- Info about Distribution?
- Ordinal
- Info about Dispersion?
- Central Tendency:
tables for median
- Dispersion: need the
inter-quartile deviation
- Frequencies: tables for
relative and absolute
- Central Tendency:
tables for median
- Info about Dispersion?
- Interval
- Info about Distribution?
- Symmetry:
calculate skewness
- Dispersion:
- Central Tendency:
- Skewed: compute the
mean and median
- Symmetric:
compute the mean
- Skewed: compute the
mean and median
- Normality:
- Normality: Kolmogorov-Smirnov one-sample test, Lilliefors
extension of Kolmogorov-Smirnov test, Chi-square
goodness-of-fit test, the Jarque-Bera test, D'Agnostino-Pearson
K-squared test, Shapiro-Wilk test. Skewness & kurtosis:
D'Agnostino-Pearson K-squared Jarque-Bera
- Normality: Kolmogorov-Smirnov one-sample test, Lilliefors
extension of Kolmogorov-Smirnov test, Chi-square
goodness-of-fit test, the Jarque-Bera test, D'Agnostino-Pearson
K-squared test, Shapiro-Wilk test. Skewness & kurtosis:
D'Agnostino-Pearson K-squared Jarque-Bera
- Frequencies:tables for relative and
absolute. Consider requesting n-tiles
- Peakedness: compute the
kurtosis of a variable
- To test departures from normality: for N greater
than 1000, refer the critical ratio of the kurtosis
measure to a table of the unit normal curve; for N
between 200 and 1000, refer the kurtosis measure
to a table for testing kurtosis; for N less than 200,
use Geary's criterion.
- To test departures from normality: for N greater
than 1000, refer the critical ratio of the kurtosis
measure to a table of the unit normal curve; for N
between 200 and 1000, refer the kurtosis measure
to a table for testing kurtosis; for N less than 200,
use Geary's criterion.
- Symmetry:
calculate skewness
- Info about Distribution?
- Nominal
- Scale of Measurement?
- 2 VARIABLES
- Scale of Measurement?
- 1 Interval,
1 Nominal
- Is interval
variable
dependent?
- YES: measure of
strength or test of
significance?
- Test of
significance:
- assuming homoscedasticity
across levels of ind. variable,
perform an analysis of variance
and F-test for significance
- With no homoscedasticity across
levels of ind. variable, use ANOVA.
For hypothesis testing use the
Welch statistic, the Brown-Forsythe
statistic, or the t-test
- assuming homoscedasticity
across levels of ind. variable,
perform an analysis of variance
and F-test for significance
- Measure of strength:
- Use the
ANOVA, and Omega Squared
Intraclass Correlation Coefficient
Kelley's Epsilon Squared
- Use the
ANOVA, and Omega Squared
Intraclass Correlation Coefficient
Kelley's Epsilon Squared
- Test of
significance:
- NO: ANOVA to perform
an analysis of variance
- YES: measure of
strength or test of
significance?
- Is interval
variable
dependent?
- 1 Nominal,
1 Ordinal
- compute the Friedman test and
probability of chance occurrence.
- Use Freeman's
coefficient of
differentiation, theta
- compute the Friedman test and
probability of chance occurrence.
- 1 Interval,
1 Ordinal
- If ordinal is based on an
underlying normally
distributed interval variable,
use Jaspen's Coefficient of
Multiserial Correlation
- If ordinal is based on an
underlying normally
distributed interval variable,
use Jaspen's Coefficient of
Multiserial Correlation
- Both Nominal
- Both variables
2-point scale?
- YES: What will
be measured?
- Symmetry: Use McNemar's test of
symmetry; it is equivalent to Cochran's Q
- Covariation: use
Yule's Q Phi
- Symmetry: Use McNemar's test of
symmetry; it is equivalent to Cochran's Q
- NO: At least one is not a
2-point scale and one
is considered an
independent variable
- Statistic based on
number of cases
in each category
- use Goodman and
Kruskal's tau b
- use Goodman and
Kruskal's tau b
- Statistic based on
number of cases in
modal categories
- calculate the asymmetric
lambdas A and B
- calculate the asymmetric
lambdas A and B
- Statistic based on
number of cases
in each category
- YES: What will
be measured?
- Both variables
2-point scale?
- Both Ordinal
- Distinction between dependent
& independent variables?
- YES: use
Somer's d for 2
ordinal variables
- NO: What do you
want to measure?
- Agreement: no applicable statistic,
but data may be transformed to
ranks and r or Krippendorff's r used
- Covariance: depending on if the
ranks are treated as interval scales,
use Kendall's tau-a, tau-b, tau-c
Goodman and Kruskal's gamma,
Kim's d, or Spearman's rho (rs)
- Agreement: no applicable statistic,
but data may be transformed to
ranks and r or Krippendorff's r used
- YES: use
Somer's d for 2
ordinal variables
- Distinction between dependent
& independent variables?
- Both Interval
- Distinction between dependent
& independent variables?
- YES: looking for
linear relationship?
- YES: use the F-test, also
computed by Regression
- NO: Curvilinear relationships- use the
F-test, computed by Regression, equal
to t-squared, for each coefficient
- YES: use the F-test, also
computed by Regression
- NO: looking for equal
means on both variables?
- YES: calculate the t-test
for paired observations
- NO: treat the relationship as linear
What do want to measure?
- Agreement: penalty
without same distribution?
- YES: Robinson's A or
the intraclass
correlation coefficient.
The test is the F-test.
- NO: Use Krippendorff's
coefficient of agreement
- YES: Robinson's A or
the intraclass
correlation coefficient.
The test is the F-test.
- Covariance:
- Use Pearson Product-Moment r (correlation
coefficient), Biserial R, or Tetrachoric r depending
on how many of the variables are dichotomous
- Use Pearson Product-Moment r (correlation
coefficient), Biserial R, or Tetrachoric r depending
on how many of the variables are dichotomous
- Agreement: penalty
without same distribution?
- YES: calculate the t-test
for paired observations
- YES: looking for
linear relationship?
- Distinction between dependent
& independent variables?
- 1 Interval,
1 Nominal
- Scale of Measurement?
- More than 2 Variables
- [Didn't Learn This]
- [Didn't Learn This]
- 1 VARIABLE
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