Exam 6 Research Psych Heinly

Cohort-Sequential Design

Two or more cohorts are observed on some measure over time.

ex: if a researcher has adolescent and adult participants and tests them multiple times over a five-year period

Single-Case Experimental Design

Participant serves as own control. Test the effect of an intervention on one subject. An advantage of this is there is a critical analysis of each individual measure.

1. Baseline Phase:

   • The baseline phase involves observing and recording the child's attention span during classroom tasks without any intervention.

   • During this phase, the teacher or researcher measures the duration of time the child stays focused on a specific task, such as reading a passage or completing a worksheet.

2. Intervention Phase:

   • In this phase, an intervention is introduced to improve the child's attention span. For example, the teacher may implement a token reward system where the child earns tokens for staying focused during tasks.

   • The intervention is applied consistently over a specified period, such as several weeks, during which data on the child's attention span are collected.

3. Outcome Evaluation:

   • The data collected during the baseline and intervention phases are compared to determine if there is a change in the child's attention span.

   • If the child's attention span increases during the intervention phase compared to baseline, it suggests that the intervention may be effective in improving attention in this specific case.

ABA Design

One participant observed in three phases 1. baseline 2. treatment 3. baseline. You can’t do stats on this data, it is visually analyzed. An advantage is the treatments may benefit participants. Disadvantage is the DV must return to baseline when treatment is removed.

1. Baseline Phase (A):

   • In this phase, the child's behavior is observed and measured without any intervention. Let's say the behavior of interest is the frequency of disruptive behaviors such as tantrums.

2. Intervention Phase (B):

   • During this phase, an intervention is implemented to target the behavior. For example, a behavior therapist might use a token economy system where the child earns tokens for positive behaviors and can exchange them for preferred items or activities.

3. Reversal Phase (A):

   • After a period of implementing the intervention (Phase B), the intervention is withdrawn or reduced, and the child returns to the baseline condition (Phase A). This phase allows researchers to see if the changes observed in the behavior during the intervention phase are indeed due to the intervention itself.

Multiple baseline design

introducing an intervention at different times across multiple behaviors, settings, or individuals to demonstrate a relationship between intervention and behavior. A disadvantage is there’s one type of treatment given.

1. Baseline Phase:

   • Alex: Baseline data collection on Alex's homework completion time for two weeks.

   • Ben: Baseline data collection on Ben's homework completion time for two weeks.

   • Claire: Baseline data collection on Claire's homework completion time for two weeks.

2. Intervention Phase:

   • Alex: Introduction of a structured homework schedule with rewards for completing tasks on time.

   • Ben: Introduction of the same structured homework schedule with rewards for completing tasks on time.

   • Claire: Introduction of the same structured homework schedule with rewards for completing tasks on time.

3. Outcome Evaluation:

   • Alex's Homework Completion Time: After implementing the intervention, Alex's homework completion time significantly decreases.

   • Ben's Homework Completion Time: Similarly, Ben's homework completion time also decreases after the intervention.

   • Claire's Homework Completion Time: Claire's homework completion time shows a similar pattern of improvement after the intervention.

Changing criterion design

Changing treatments to a situation. They administer successive treatments in one participant, changing criterion as often as needed.

1. Baseline Phase:

   • The student's baseline reading fluency is assessed by measuring the number of words read correctly per minute (WCPM) in a passage.

2. Intervention Phase with Changing Criteria:

   • Initial Criterion: The intervention phase begins with an initial criterion set at 50 WCPM. The student receives instruction and practice focused on improving reading fluency.

   • First Criterion Change: Once the student consistently meets or exceeds the initial criterion of 50 WCPM over several sessions, the criterion is increased to 70 WCPM.

   • Second Criterion Change: After meeting the 70 WCPM criterion consistently, the criterion is further increased to 90 WCPM.

   • Third Criterion Change: Finally, the criterion is raised to 110 WCPM.

3. Outcome Evaluation:

   • The student's progress is assessed at each criterion level to determine if they meet the new target. If the student consistently meets or surpasses the set criterion, it indicates successful improvement in reading fluency.

Within-subjects design

All the same people in both conditions. For example instead of our chunking presentation and research presentation being given to separate groups, it would instead be given to the same group.

Reasons to observe the same participants in each group (in a within-subjects design)?

You can manage the sample size, you need less people to have robust states. You can observe changes over time since it’s the same people. An issue though, is randomization is not possible in this kind of design.

Time related factors

Potential confounders, issues across levels of the iv during time related studies threaten internal validity.

Time-related factors examples

• Maturation: there’s time effects between time related studies.

• Testing effects: Participants not knowing how they are being tested or what they’re being tested on.

• Participant fatigue: Participants can simply just get tired.

Heinlys malingering study

People with illnesses split into malingering and non-malingering groups. How do people in pain compare to people with actual cognitive impairments. Independent measure: processing

Strategies to control for order effects

counterbalancing

Control timing

Counterbalancing

In complete counterbalancing, all possible orders of presenting stimuli or conditions are used across participants (All get: ABC, ACB, CBA). Partial counterbalancing is used when the number of possible orders is too large to present all combinations feasibly or when certain orders are considered more critical than others (one gets: ABC, ACB, CBA)

How to control timing

Control interval between treatments or groups to minimize possible testing and carryover effects. Minimize the demands places on participants and decreases the likelihood of participant fatigue.

Between subject designs

Randomization, this is what our study was.

Factorial Design

Design where participants are observed across the combination of levels of two factors. Looking at blue vs. red vs arial vs time new roman vs 14 pt vs 16 pt. A complete factorial design is when each level of ONE factor is combined in each cell or combination of levels.

Types of factorial designs

Between subjects: diff subjects

within subjects: same subjects

mixed factorial: combination of both.

Interaction effects

2 variables together can create a larger effect than alone.

Main effect

Overall effect of an independent variable in a complex design, this can only be one thing. Effect on DV if only that independent variable is looked at.

Interactions

the combined effects of two or more factors on the response variable.

Two way anova

When were adding on multiple independent variables were doing 2 way anovas or 3 way anovas (depending on amount of variables)

Error

Individual differences (individual differences in participant scores). Instead of means of results it’s much more specific.

Why are graphs useful when looking at main effects and interactions?

It can help us visually identify a difference between the variables but to know if it’s a significant difference we would have to do an anova.

What does it mean lines are not parallel when graphing main effect?

There’s a possible interaction between variables.

What design can we use if we have preexisting or quasi-independent factors??

Use factorial designs.

Participant variable

any characteristic or aspect of a participant's background that could affect study results, even though it's not the focus of an experiment

Ex: personality type in a study about stress coping.

Why should we include two or more factors in an experiment?

to build on previous research and potentially find something new about it. To control for threats of validity which can instead be used at factors. to enhance the informativeness of interpretation which allows us to analyze the effects of two or more factors simultaneously.

Higher order factorial design and higher order interaction.

Design with more than 2 factors. Interaction of two or more factors.