PSY 689 Week 4 Data Analysis: Statistical
Table Assignment | 2025 Update with
complete solutions.
Construct Validity ...ANSWER...- *Are you actually studying what you are supposed to
be studying?*
-"The whole truth and nothing but the truth."
- The extent to which a set of empirical measures provides a selective and exhaustive
estimate of the target theoretical variables.
External Validity ...ANSWER...- The extent to which the results of the experiment can be
generalized to other people, places, and times, rather than being attributed to one
specific case.
Internal Validity ...ANSWER...- The extent to which the observed pattern of results is
due to the causal relationships between the variables and not caused by external forces
or confounds ("third variables").
- Objective, never theoretical.
- All threats to internal validity are confounds.
- In context of experiments, internal validity is the extent to which the pattern observed
in the DV is due to the causal effect of the IV. Any variable that varies systematically
with IV.
Statistical (Conclusion) Validity ...ANSWER...- The extent to which conclusions about
the relationship among variables based on the data are correct and/or reasonable.
- Also the extent to which inferences based on a sample provide accurate estimates of
the sampling population.
,Correlational Study Approach vs. Experimental Study Approach ...ANSWER...-
Correlational is better for external validity
Experimental is better for internal validity
The 3 Criteria for a Causal Claim ...ANSWER...- Referred to as *covariance, temporal
precedence,* and *internal validity.*
- The only way *sustain* a causal claim is to have an association of some sort, evidence
of temporal precedence, and internal validity. Only then do you have sufficient evidence
to (publicly) *claim* a relationship.
Criteria for Causal Claim: Covariance ...ANSWER...- There needs to be an association
of some sort between the cause and the effect (e.g., a correlation or a difference
between conditions).
- The putative (generally considered) cause and effect must show some relationship;
e.g., have a significant (linear) correlation.
- Established by *any* consistent and significant relationship.
- *Ex:* A covariance association establishes that *A* can *cause B* and *B* can also
*cause A*.
Criteria for Causal Claim: Temporal Precedence ...ANSWER...- The putative cause
must precede the effect.
- This is established either by two general methods: an experiment or a cross-lagged
study.
- *Ex (directionality problem):* Do we know which came first in time? Did *A come
before B* or did *B come before A*? (If we cannot tell which came first, we cannot infer
causation.)
Does Temporal Precedence deal with the 3rd variable problem? ...ANSWER...No! It
could still be spurious.
Criteria for Causal Claim: Internal Validity ...ANSWER...- Alternative explanations of the
association need to be ruled out.
, - I.E., the covariation must still be found when other variables are "controlled" (either
experimentally or statistically)
- *Ex (3rd-variable problem):* Is there a *C* variable that is associated with both *A* and
*B*, independently? (If there is a plausible 3rd variable, we cannot infer causation.)
The 3 Types of Claims ...ANSWER...1) *Frequency*: Univariate statement of fact; e.g.,
the mean BDI score of undergraduates.
2) *Association*: Bivariate (or larger) statement of fact (correlation); e.g., the correlation
between BDI (depression) and HAM (anxiety).
3) *Causal*: An explanation for an observed association; e.g., depression causes
anxiety.
Cross-Lagged Correlation/Study ...ANSWER...- Where you measure the variables of
interest (*the cause* and *the effect*) at two or more points in time to establish temporal
precedence.
- Basically, two cross-sectional correlations make one cross-lagged correlation.
Steps of a Cross-Lagged Study ...ANSWER...1) *Prelim #1*: The cause and the effect
should be correlated with each other at least in earlier time-points, which are *cross-
sectional correlations*. *You must make sure they're correlated at time one*.
2) *Prelim #2*: The cause and the effect should be correlated with ITSELF across the
time points, which are *autocorrelations*.
3) *Critical Test*: The cause should be correlated with future values of the effect...and
this correlation should be stronger than that between the effect and future values of the
cause.
Cross-Sectional Correlation ...ANSWER...- The 1st preliminary of cross-lagged studies.
- *It is when the cause and effect should be correlated with each other across time, at
least at the earlier time-point(s).*
- It can sum up to "at one time."
Autocorrelations ...ANSWER...- In cross-sectional, the measures are correlated with
themselves across time.
Table Assignment | 2025 Update with
complete solutions.
Construct Validity ...ANSWER...- *Are you actually studying what you are supposed to
be studying?*
-"The whole truth and nothing but the truth."
- The extent to which a set of empirical measures provides a selective and exhaustive
estimate of the target theoretical variables.
External Validity ...ANSWER...- The extent to which the results of the experiment can be
generalized to other people, places, and times, rather than being attributed to one
specific case.
Internal Validity ...ANSWER...- The extent to which the observed pattern of results is
due to the causal relationships between the variables and not caused by external forces
or confounds ("third variables").
- Objective, never theoretical.
- All threats to internal validity are confounds.
- In context of experiments, internal validity is the extent to which the pattern observed
in the DV is due to the causal effect of the IV. Any variable that varies systematically
with IV.
Statistical (Conclusion) Validity ...ANSWER...- The extent to which conclusions about
the relationship among variables based on the data are correct and/or reasonable.
- Also the extent to which inferences based on a sample provide accurate estimates of
the sampling population.
,Correlational Study Approach vs. Experimental Study Approach ...ANSWER...-
Correlational is better for external validity
Experimental is better for internal validity
The 3 Criteria for a Causal Claim ...ANSWER...- Referred to as *covariance, temporal
precedence,* and *internal validity.*
- The only way *sustain* a causal claim is to have an association of some sort, evidence
of temporal precedence, and internal validity. Only then do you have sufficient evidence
to (publicly) *claim* a relationship.
Criteria for Causal Claim: Covariance ...ANSWER...- There needs to be an association
of some sort between the cause and the effect (e.g., a correlation or a difference
between conditions).
- The putative (generally considered) cause and effect must show some relationship;
e.g., have a significant (linear) correlation.
- Established by *any* consistent and significant relationship.
- *Ex:* A covariance association establishes that *A* can *cause B* and *B* can also
*cause A*.
Criteria for Causal Claim: Temporal Precedence ...ANSWER...- The putative cause
must precede the effect.
- This is established either by two general methods: an experiment or a cross-lagged
study.
- *Ex (directionality problem):* Do we know which came first in time? Did *A come
before B* or did *B come before A*? (If we cannot tell which came first, we cannot infer
causation.)
Does Temporal Precedence deal with the 3rd variable problem? ...ANSWER...No! It
could still be spurious.
Criteria for Causal Claim: Internal Validity ...ANSWER...- Alternative explanations of the
association need to be ruled out.
, - I.E., the covariation must still be found when other variables are "controlled" (either
experimentally or statistically)
- *Ex (3rd-variable problem):* Is there a *C* variable that is associated with both *A* and
*B*, independently? (If there is a plausible 3rd variable, we cannot infer causation.)
The 3 Types of Claims ...ANSWER...1) *Frequency*: Univariate statement of fact; e.g.,
the mean BDI score of undergraduates.
2) *Association*: Bivariate (or larger) statement of fact (correlation); e.g., the correlation
between BDI (depression) and HAM (anxiety).
3) *Causal*: An explanation for an observed association; e.g., depression causes
anxiety.
Cross-Lagged Correlation/Study ...ANSWER...- Where you measure the variables of
interest (*the cause* and *the effect*) at two or more points in time to establish temporal
precedence.
- Basically, two cross-sectional correlations make one cross-lagged correlation.
Steps of a Cross-Lagged Study ...ANSWER...1) *Prelim #1*: The cause and the effect
should be correlated with each other at least in earlier time-points, which are *cross-
sectional correlations*. *You must make sure they're correlated at time one*.
2) *Prelim #2*: The cause and the effect should be correlated with ITSELF across the
time points, which are *autocorrelations*.
3) *Critical Test*: The cause should be correlated with future values of the effect...and
this correlation should be stronger than that between the effect and future values of the
cause.
Cross-Sectional Correlation ...ANSWER...- The 1st preliminary of cross-lagged studies.
- *It is when the cause and effect should be correlated with each other across time, at
least at the earlier time-point(s).*
- It can sum up to "at one time."
Autocorrelations ...ANSWER...- In cross-sectional, the measures are correlated with
themselves across time.
