Topic 3 Research Design: An Overview

Question 1

What is a Research Design

Answer 1

the overall strategy that you choose to integrate the different components of the study in a coherent and logical way
- plan for answering a research question using empirical data

Method-> design

Question 2

Quantitative + Qualitative

Answer 2

Focus

Quan = specific beh that ben easily quantified (questionnaires)
Quali= people beh in natural settings and describing their world in their own words (discussions)

Objective

Quan= quantify data and generalise results from a sample to understand the population of interest -> track data over time
Qual= understanding underlying reasons or motivations -> provide insight into setting of a problem

Question 3

HOW MUCH Sample and data collection FOR QUAN AND QUAL STUDIES

Answer 3

Quan = LArge and broad, statistically projectable
- standardised instruments, operation of variables

Qual = small and narrow, not statistically projectable
- adapted to the situation, variables not defined in advance

Question 4

types of quantitative research
types of qualitive design

Answer 4

Quan
- experimental
-> true-experimental
— Iv manipulated
— random assignment
— Control group or multiple measure
-> quasi-experimental
— Iv manipulated
— NOT random assignment
— Control group or multiple measure
-> single-subject
— IV manipulated
- non-experimental
-> Analytical/correlational (w comparison)
-> Descriptive (w/out)

 survey studies, naturalistic/ecology, meta-analysis study, case-study 

qual
- ethnography, case study, historical, in-depth interview, document review

Question 5

observational methods
objectives, methods, issues

Answer 5

naturalistic objectives, methods, issues (qualitative)
-> complete accurate picture of what happened in setting
-> keep detailed field of notes, write or dictate on a regular basis
-> subectivity, alteration of results if not concealed observation, time consuming

Systematic objectives, methods, issues (quantitative)
-> obs. of a specific beh in a setting, develop hypothesis
-> coding systems: decide which behaviors are of interest, choose a setting, observe and codify
-> equipment, reactivity, reliability

Question 6

quan - Experimental -> true experiment

Answer 6

goal> psych to understand human beh - accurately describe causal underpinning - predict beh

-> cause-effect relationship
-> using predictive analytics
is the use of statistical algorithms to identify the likelihood of future outcomes based on data
-> having high internal validity
estabilish trustworthy v relationship (eliminate alt explanations)

Question 7

quan - Experimental -> true experiment 2

Answer 7

Maximise independent variance
Minimize error
controlling external variable

-> large samples outcomes predicted by chance have a Normal (Gaussian) distribution (bell shaped curve)

mean = average outcome
other outcomes are distributed around the mean
-> outcomes gets smaller

Question 8

variance

Answer 8

variance is the amount that scores vary around the mean score (SHOULD BE SIMILAR BETWEEN THE GROUPS)
= HOMOgeneity (sameness) of variance
= non-homogeneity of variance => if they are not similar, it might affect the validity of the outcome. Statistical significance is often based on how much the scores vary

Question 9

How do we minimise error variance / controlling external variable?

Answer 9

• large group of participants
• suitable measuring instruments
• rigorous research planning
• balancing the design
• removal of outliers
• assumption of normality

Question 10

controlling external variables - balancing the design

Answer 10

balanced designs have equal numbers of observation for all possible level combinations - compared to unbalanced

balance 30 - 30 - 30
unbalanced 30 - 28 - 30

Question 11

controlling external variables - removal of outliers

Answer 11

def - data points that significantly differ from other observations. They can arise from data variability or measurement errors, potentially skewing results and leading to inaccurate conclusions. Identifying :
-> visualise :
Box Plots - Show the spread of data points to identify outliers.
Scatter Plots - Visualize relationships between variables to spot outliers.

-> statistical methods
Z-Scores - Calculate the z-score for each data point; values beyond ±3 are typically outliers.
Interquartile Range (IQR) - Calculate IQR (Q3 - Q1). Points below Q1 - 1.5IQR or above Q3 + 1.5IQR are considered outliers.
-> automated detection
Automated Detection - Use algorithms like DBSCAN to detect outliers based on data distribution.

Question 12

Controlling external variable - Assumption of normality

Answer 12

When the data do not have a normal distribution. A possible way to fix this is to apply a statistical transformation. Transforming data is a method of changing the distribution by applying a mathematical function to each participant’s data value. -

like log transformation for a positively skewed to a normal distribution

exponential transformation for a negatively skewed residual to a normal distribution

Question 13

DEFINING THE EXPERIEMENTAL METHOD

Answer 13

• cross-sectional studies
  different group of people are tested at the same time and their results are compared. Quick to carry out, easily replicated to test the reliability of the findings
• longitudinal studies
  participants are studied over a long period of time -> track development, monitor changes over time
• cohort studies
  several groups are studied over a long period of time
  example
  exposed -> ->
  time passes compare
  not exposed -> ->

Question 14

Within-subject

Answer 14

each participant takes part in all experimental conditions

Question 15

between-subject

Answer 15

each participant takes part in one experimental condition

Question 16

Random assignment to experimental conditions

Answer 16

benefit:
-eliminates the selection bias
-balances the groups with respect to many known and unknown confounding or prognostic variables
-> randomised an experiment is essential for testing the efficacy of the treatment

in a clinical research, if treatment groups are systematically different, research results will be biased

Question 17

Quasi-experimental design

Answer 17

Anything less is quasi-experimental (‘‘almost’’ experimental). In general, a quasi-experiment exists whenever causal conclusions cannot be drawn because there is less than complete control over the variables in the study, usually because random assignment is not feasible.
-> Impossibility of creating experimental conditions: single-group studies.

aim:
― Analytical-predictive objectives
― Impossibility to control confounding variables
― Reduced internal validity (because extraneous variables are not held constant)

The quasi-experimental, sometimes called the pre-post intervention design is often used to evaluate the benefits of specific interventions.

Question 18

Single-subject

Answer 18

Individual “case” is the unit of intervention and unit of data analysis; The case provides its own control for purposes of comparison.

example
-> Management at an electric fry pan company is testing a flextime schedule to boost productivity by improving morale. Pittsburgh plant adopts flextime, Cleveland plant maintains the regular schedule. Productivity in both plants will be measured and compared to evaluate the effect.

Question 19

Correlational vs experimental

Answer 19

C: concerned with investigating the relationships between naturally occurring variables and with studying individual differences

E: interested in minimising or controlling these differences in order to show that some stimulus factor influences beh

Question 20

Analytical/ correlations study

Answer 20

Positive correlations
both vs increase or decrease at the same time

negative correlations
as the amount of one variable increases the other decreases

no correlation
there is no relationship between the two v

Question 21

correlation coefficient (r)

Answer 21

A correlation coefficient is a statistic that describes how strongly variables are related to one another

P r provides info about the strength of the relationship and the direction of the relationship

0.8< r < 1 STRONG
0.5 < r < 0.8 moderate
< 0.5 WEAK

The Pearson correlation coefficient (r) is designed to detect only linear relationships. -> curvilinear relationship

Question 22

Common approaches in correlationational research
- survey study
- archival data
- content analysis

Answer 22

-> method for collecting information or data as reported by individuals. Administered to research participants who answer the questions themselves
-> data that has already been collected for another purpose Newspapers, census data, institutional records, hospital records
-> Analyze spoken or written record

Question 23

Common approaches in correlational research
-> meta-analysis
-> case study

Answer 23

-> Statistical procedure combining data from multiple studies
Systematic and quantitative, combines data in order to provide information about effect sizes
— Identify studies ; Determine eligibility of studies ; Get the data from these studies ; Statistically analyze the data

-> The case study research design is useful for testing whether scientific theories and models actually work in the real world. (CREd library - clinical research education)
single-subject design vs. case studies

Question 24

Common approaches in correlational research
- Systematic observation

Answer 24

Make observations in a natural environment - Utilizes coding- target behaviors are specified and then watched

Question 25

Rank of internal validity

Answer 25

In order of lowest internal validity to highest: Correlational (low)
Quasi-experimental (moderate) Experimental (high)

Question 26

DESCRIPTIVE STUDY
-> freq. distribution
-> descriptive study

Answer 26

-> (when analysing data) A frequency distribution indicates the number of individuals who receive each possible score on a variable
-> DS allows scientists to make precise statements about the data

=> central tendency - mean, median, mode (most freq score)
=> variability - standard deviation (ave. deviation of scores from mean)

Question 27

QUALITATIVE RESEARCH - ethnography

Answer 27

-> prolonged study of an intact culture in its normal setting. the researcher gather primarily observational data

not a static design, wherein the categories [or themes described by the participants] develop during the study

Question 28

QUALITATIVE RESEARCH - case study

Answer 28

-> The researcher explores a single entity or phenomenon (‘the case’) bounded by time and activity (a program, event, process, institution, or social group)

collects detailed information by using a variety of data collection procedures

-> Phineas Gage
pole through skull (the denotation that the accident in the frontal brain affected his personality entirely)

Question 29

QUALITATIVE RESEARCH
- Historical

Answer 29

The use of historical data to answer a question
-> systematic collection and objective evaluation of data related to past occurrences in order to test hypotheses concerning causes, effects, or trends of these events that may help to explain present events and anticipate future events

Question 30

QUALITATIVE RESEARCH
- In-depth interview
- document review

Answer 30

-> Conducting intensive individual interviews with a small number of respondents to explore their perspectives on a particular idea, program, or situation.
-> Documents are interpreted by the researcher to give voice and meaning around an assessment topic. Analyzing documents incorporates coding content into themes similar to how focus group or interview transcripts are analyzed.

Question 31

Literature Review, Systematic Review, Meta-analysis, Umbrella review

Answer 31

• comprehensive summary of all the knowledge available on a specific topic. It involves reading and synthesizing the findings from various sources like books, articles, and other research papers.
• detailed and comprehensive review of existing literature using a structured and predefined method. It aims to minimize bias by using a systematic approach to search, appraise, and synthesize research evidence.
• statistical technique used within a systematic review to combine the results of multiple studies. It provides a more precise estimate of the effect size by pooling data.
• (overview of reviews) synthesizes data from multiple systematic reviews and meta-analyses on a broad topic.