Ex Post Facto Design Flashcards
(29 cards)
What does ex pos factor mean and what is it used for?
1) ex post facto = after the fact, in latin it means “from a thin done afterwards”. 2) It attempts to determine a cause-and-effect relationship between an independent v. and dependent v. 3) The group of participants are determined by pre-existing conditions
How is the independent variable in ex post facto design?
1) it is not manipulated, rather observed as it naturally occurs. 2) it consists of pre-existing conditions or characteristics (exist before the study) 3) and historial events or circumantances (events and conditions that have already happened NOT UNDER THE CONTROL OF THE RESEARCHER).
What are the characteristics of this design?
1) no manipulation of IV 2) limitied vontrol over extraneous variables 3) exploratory and descriptive + They cannot establish causal relaitonships due to the lack of experimental manipulation
Why does it have low internal validity?
1) Because this design has no control over the IV and they also they cannot manipulate it.
What does it internal validity mean and how can this design have any advantage without internal vaility?
1) It is the degree to which we can establic causal relationships, rejecting alternative explanations. 2)This allows the researched to study phenomena that cannot be manipilated intentionally due to ethical or practical limitations
How can we compensate for the lack of control over extraneous variables?
1) Matching 2) ANCOVA 3) Introduction of v realted to the dv
How does matching help the lack of internal validity?
By creating comparable groups based on key characteristics, helping ensure differences in outcomes are more likely due to the variable of interest.
How does ANCOVA help the lack of internal validity?
1) it incorporates covariates into the statistical analysis to remove their effect on the dv. 2) Helping to clarify the role of the independent variable controling for the influence of extraneous variables. 3) Allows for researchers to statistically adjust for the effects of covariates, this enhances the ability to isolate the impact of the IV on the DV (increasing validity)
How does introducing of variables related to the dependent v. help the lack of internal validity?
We can approach a more accurate interpretation of the relationship between variables, concluding with more cofidence the relationship between variables.
TYPES OF EX POST FACTO DESIGN: single case with relational purpose
1) Using a single sampe of participants, this design focuses on understanding how variables are related to eachother by calculating correlations (not establishin causality). 2) This sample can be large and each partic. can be measured on 2 or more variables. 3) This study is primarily descriptive and exploratory aiming to uncover patterns or associations between variables within the group.
TYPES OF EX POST FACTO DESIGN: single case with predicitive purpose
1) This case is used when we already know about the problem being studied. 2) We use that relationship to create predicitive models (using the IV to predict the DV)
TYPES OF EX POST FACTO DESIGN: Group comparision design (genrally)
1) Depending on how participants are chosen groups can be retrospective or prospective. 2) Retrospective are groups based on the DV (simple AND/OR case-control) 3) Prospective groups based on the independent v. (simple, complex or factorial, evolutionary)
TYPES OF EX POST FACTO DESIGN: Group comparision design: Retrospective simple
A single group with the same outcome (DV) is studied to identify shared prior factors (IVs).
Example: Studying students with depression to see if they experienced bullying.
Weak internal validity: many other unmeasured variables might explain the outcome.
TYPES OF EX POST FACTO DESIGN: Group comparision design: Retrospective case-control design
Compares two groups: one with the outcome (cases) and one without (controls).
Aims to find past factors (IVs) that differ between the two groups and may explain the outcome.
Groups must be similar except for the DV; allows use of correlational analysis.
TYPES OF EX POST FACTO DESIGN: Group comparision design: Prospective Simple Design (Group Comparison)
Participants are grouped based on values of one IV, before the DV is measured.
At least two groups are formed (one per IV value), and DV is later assessed.
Since IVs are not manipulated and extraneous variables may exist, causality cannot be confirmed.
Techniques like matching or ANCOVA may help control for extraneous variables.
TYPES OF EX POST FACTO DESIGN: Group comparision design: Prospective Complex (Factorial) Design
Involves multiple IVs and one or more DVs.
Participants are selected based on combinations of IV values (not randomly assigned).
Similar to factorial experimental design, but without manipulation of IVs.
Uses multifactorial ANOVA for data analysis.
TYPES OF EX POST FACTO DESIGN: Group comparision design: Types of Prospective Designs – Overview
Longitudinal Study: Same individuals followed over time → tracks change.
Cross-Sectional Study: One-time snapshot of a population → identifies correlations.
Sequential Study: Combines both – studies different age groups over time.
TYPES OF EX POST FACTO DESIGN: Group comparision design: Prospective Design – Bias & Effects
Longitudinal: Prone to history effects (events influencing participants), but avoids cohort effects.
Cross-Sectional: Avoids history effects but confuses age vs. generation (cohort effect).
Sequential: Avoids both history and cohort effects, allowing clearer analysis over time and age.
Retrospective Study Designs – IV vs. DV Selection
Selecting the IV:
Use when you’re interested in a shared characteristic or past event (e.g., a cohort exposed to something).
→ Cohort Retrospective Study
Selecting the DV:
Use when focusing on a specific outcome and looking for possible past causes.
→ Case-Control Retrospective Design
Type of Relationships Explored:
DV: Cancer → IV: Early exposure to radiation/tobacco
DV: Insomnia → IV: Poor sleep hygiene in childhood
IV: Exposure to disinformation during COVID → DV: Risk behaviors or persistent COVID
Cross-Sectional Comparative Design
Cross-Sectional Cohort:
Focuses on cohorts to study prevalence, epidemiological patterns, or sociodemographic characteristics at a specific point in time.
Natural Groups:
Explores individual differences (e.g., age, gender) by selecting groups based on stable IVs.
Can be transcultural if studying the influence of culture.
Cross-Sectional Prospective Designs
Simultaneous Cross-Sectional Design: Compares two samples that differ in age or maturity at the same time point. Allows between-subject comparisons, not within-subject.
Repeated Cross-Sectional Design (Trend Study): Same population type, different individuals over time (e.g., surveying Research Design students in 2024, 2025, 2026).
Repeated Measures & Cohort Designs
Repeated Measures Prospective Design: Measures the same group multiple times to analyze within-group changes over time.
Prospective Cohort Design: Follows a specific subgroup (cohort) over time to assess the incidence or development of a variable. Can include internal controls or a separate unexposed cohort.
Nested Case-Control Study
Special type of prospective comparison within a cohort.
Selects cases and controls from a well-defined group based on shared characteristics.
Tracks a specific outcome over time; cost-effective and improves validity.
Evolutive Designs – Overview
Used when age, development, or time is the key variable.
Aim: Understand how presence/absence of traits influences other variables across developmental stages.
Can be cross-sectional, longitudinal, or sequential depending on how the sample is tracked.
