Evaluation design III

Question 1

Quasi-experimental designs

Answer 1

Can be used when random assignment is not possible

Less internal val than “true” exps

Still provide moderate amount of support for causal inferences

Question 2

Quasi-experimental designs research

Answer 2

Sharma et al. (2021)

Question 3

Sharma et al. (2021)

Answer 3

BackgroundAccredited Social Health Activists (ASHA) are community health workers responsible for improving the health status of people by facilitating their access to healthcare services. The life skills of ASHA are known to be effective in negotiating behaviour change in the community; however, there has been a meagre focus towards improving them. Considering this gap, we adopted a comprehensive training program, known as Personal Advancement and Career Enhancement (P.A.C.E.), to empower ASHAs on life skills and financial literacy. The present study intends to assess the training program in two districts of Uttar Pradesh, India, by examining changes in knowledge, perceptions, and practices of ASHAs about life skills and financial literacy.

MethodsWe conducted a quasi-experimental, non-randomized, controlled study with pre-and post-test assessments. Data were collected on socio-demographic characteristics, knowledge, and practices related to life skills (communication skills, self-confidence, problem-solving and decision-making skills, time and stress management skills) and financial literacy. Additionally, change perceptions on gender-, life skills-, and savings-related practices at the personal, community, and workplace levels were assessed in the intervention group. Factor analysis was performed to obtain the change patterns by assessing the degree to which the four life skills, financial literacy, and change perceptions on practices were correlated. A general linear regression model was performed to assess associations among change pattern scores and socio-demographic variables.

ResultsWe analyzed the data of 171 ASHAs (intervention group:86 and control group:85). There was a significant improvement in the average post-test scores of all the life skills and financial literacy in the intervention group (p<0.001). Three distinct change patterns were found post-training in the intervention group. Factor 1 (high loadings for change perceptions on practices) was positively associated with ASHAs aged 38 and above and with experience of 12years. On the contrary, the change in financial literacy and self-confidence scores was common among ASHAs with more than 12years of experience.

ConclusionsThe P.A.C.E training program was found effective in improving the life skills and financial literacy of ASHAs in India

Question 4

Controlled before and after study design

Answer 4

see notes

Question 5

Controlled before and after study design research

Answer 5

Goga et al. (2020)

Question 6

Goga et al. (2020)

Answer 6

Objectives We report the effectiveness of a mentoring approach to improve health workers’ (HWs’) knowledge, attitudes and confidence with counselling on HIV and infant feeding.

Design Quasi-experimental controlled before-after study. Setting Randomly selected primary healthcare clinics (n=24 intervention, n=12 comparison); two districts, South Africa.

Participants All HWs providing infant feeding counselling in selected facilities were invited.

Interventions Three 1-2 hours, on-site workshops over 3-6 weeks. Primary outcome measures Knowledge (22 binary questions), attitude (21 questions-5-point Likert Scale) and confidence (19 questions-3-point Likert Scale). Individual item responses were added within each of the attitude and confidence domains. The respective sums were taken to be the domain composite index and used as a dependent variable to evaluate intervention effect. Linear regression models were used to estimate the mean score difference between intervention and comparison groups postintervention, adjusting for the mean score difference between them at baseline. Analyses were adjusted for participant baseline characteristics and clustering at health facility level.

Results In intervention and comparison sites, respectively: 289 and 131 baseline and 253 and 114 follow-up interviews were conducted (August-December 2017). At baseline there was no difference in mean number of correctly answered knowledge questions; this differed significantly at follow-up (15.2 in comparison; 17.2 in intervention sites (p<0.001)). At follow-up, the mean attitude and confidence scores towards breast feeding were better in intervention versus comparison sites (p<0.001 and p=0.05, respectively). Controlling for confounders, interactions between time and intervention group and preintervention values, the attitude score was 5.1 points significantly higher in intervention versus comparison groups.

Conclusion A participatory, low-intensity on-site mentoring approach to disseminating updated infant feeding guidelines improved HWs’ knowledge, attitudes and confidence more than standard dissemination via a circular. Further research is required to evaluate the effectiveness, feasibility and sustainability of this approach at scale.

Question 7

types of controlled conditions in quasi-exp design

Answer 7

Control group in quasi-exp study may receive diff intervention, selected components of intervention being tested/something that mimics time and attention paid to Ps (i.e. placebo)

Or use wait-list control, which means control Ps receive nothing during study period but will eventually receive intervention some time after study period

Question 8

the cycling demo towns programme

Answer 8

1st phase: Oct 2005-Oct 2008

All towns funded at approx. £6 per head per year, matched by local authority

All towns ‘medium-sized’; larger ones focused effort on part of popn
○ Exeter one of towns

Infrastructure changes - painting cycling lanes

Campaigns

Ride as groups

Media coverage

Signage

Question 9

surveys

Answer 9

Secondary analysis of Sport England’s Active People Survey (2005/5 and 2007/8)

Sport and active recreation
○ APS1 (2005/6) n = 1000 per LA (local authority)
○ APS2 (2007/8) n = 500 per LA
○ Phone; random digit dialling; representative sample
○ Didn’t necessary take part in campaign
- Intervention designed to affect whole popn level not just those P in intervention - should have sufficient reach to affect all of local authority

see notes

Left: at baseline 10-12% cycled at least once per month - equality at baseline - more variation in demonstration compared to other authorities - due to larger sample size - increase in cycling prevalence in 2008 with demonstration group - smaller change in non intervention - error bars don’t overlap - there is effect of intervention

Right: higher standard of cycling - lower prevalence - 2.5% - increases more in demo towns than non demo towns - bigger error bars -overlap - diffs not sig - less of change than if cycled less freq

Question 10

Matched analysis

Answer 10

Possibility of confounders, e.g. age, gender

CDTs matched with comparison areas using National Statistics 2001 Area Classification

Closest stat neighbour on demographics

see notes

Closer r’ship in before and after with just once a month - closer r’ship with matched groups

Error bars overlap - just by chance

Question 11

Matched analysis research

Answer 11

Rose and van der Laan (2009)

Question 12

Rose and van der Laan (2009)

Answer 12

Matched case-control study designs are commonly implemented in the field of public health. While matching is intended to eliminate confounding, the main potential benefit of matching in case-control studies is a gain in efficiency. Methods for analyzing matched case-control studies have focused on utilizing conditional logistic regression models that provide conditional and not causal estimates of the odds ratio. This article investigates the use of case-control weighted targeted maximum likelihood estimation to obtain marginal causal effects in matched case-control study designs. We compare the use of case-control weighted targeted maximum likelihood estimation in matched and unmatched designs in an effort to explore which design yields the most information about the marginal causal effect. The procedures require knowledge of certain prevalence probabilities and were previously described byvan der Laan (2008). In many practical situations where a causal effect is the parameter of interest, researchers may be better served using an unmatched design.

Question 13

Changes in cycling between 2006-2009: ICM matched analysis (n=c.9,000)

Answer 13

Mean time spent cycling 1.23h-1.25h

% cycling in past year: 24.3%-27.7%

New to cycling: 1.8%-2.8%
○ Only people who respond may already cycle already

Cycled in last 7 days: 41.7%-49.4%

No sig change: mean days in last week; mean time in last week; % ride to work; days cycled to work

Question 14

Changes in cycling between 2006-2009: ICM matched analysis (n=c.9,000) research

Answer 14

Sustrans and Davis (2019)

Question 15

Sustrans and Davis (2019)

Answer 15

intervention typologies:
§ City and town wide interventions
§ Building or improving routes or networks
§ Social marketing including marketing of infrastructure
§ Workplace and other institution based interventions
§ Interpersonal interventions
§ School based interventions

We distinguish city and town wide interventions from the other intervention typologies by virtue of the fact of the approach applied being usually a combination of measures. These combinations typically include measures included in the other typological clusters. The other groups of identified typologies tend, in the research literature and in the practicality of delivery, to be relatively more localised.

Overall, the review concludes that there is strong evidence for the positive impact of interventions to increase active travel. This in turn increases levels of physical activity 13 15 . Of the different intervention typologies the evidence was strongest (in terms of volume and robustness) for city or town-wide interventions. Each of the other intervention types reported some increases in walking and or cycling.

Question 16

Quasi-experimental statistical methods

Answer 16

Diff-in-Diff analysis: method involves comparing changes before and after the programme for indvs in programme and control

Regression analysis: attempts to address problem of confounding by controlling for diff at baseline

Question 17

Quasi-experimental statistical methods research

Answer 17

Nygaard et al. (2020)

Question 18

Nygaard et al. (2020)

Answer 18

Often an intervention is applied in an area (e.g. community, municipality) without it being an experiment and without a control group, this can be categorized as a natural experiment. Such a situation offers the opportunity to exploit exposure contrasts between areas regarding the specific intervention for evaluation. In the present study, we will employ the difference-in-difference approach to evaluate the natural experiment (the structural intervention) comparing measures of health and social factors retrieved from registers in the two social housing areas before and after the intervention. A ‘natural experiment’ study comparing individual and aggregated level differences in register-based information on health and social variables across time including the entire study period is included in the research project. The population includes all residents with an address in the study area and the control area at any point during the years 2015-2025 (∼3,000 residents in each area). All residents are linked to the Danish social and health registers by the unique personal identification number, which makes it possible to follow all permanent and former residents over time. Hereby we plan to study if the structural changes (the structural intervention, the ‘natural experiment’) give rise to differences in health (such as use of general practitioner, hospitalizations, use of selected medications) and social factors (e.g. divorces, income levels, unemployment) compared to the control area. The control area is representing a similar social housing area in the same municipality, which will not undergo structural changes until 2023. Findings will be evaluated drawing upon knowledge gained from the entire study from surveys and qualitative interviews as well experiences from the interventions. In this presentation, we wish to discuss how best to include the knowledge based on other methodologies in the register-based analyses

Question 19

advantages of controlled before and after design

Answer 19

Provides some assurance that outcomes actually results of programme

Most practical option for conducting outcome evals in community interventions

By using preexisting/self-selecting groups, such as indvs already enrolled in programme, it avoids additional steps required with random assignment to study conditions

Overcomes ethical concerns involved in withholding/delaying treatment/substituting less effective treatment for one group of study Ps

Question 20

disadvantages of controlled before and after design

Answer 20

Can demand more time and resources

Requires access to at least 2 similar groups

Without randomisation, study groups may differ in imp ways that account for some of groups diffs in outcomes after intervention

Selection bias

Question 21

Interrupted time series design

Answer 21

Helpful for overcoming secular trends - what is going on in background with prevalence of outcome interested in

see notes

May be other factors that explain deviation

Question 22

Interrupted time series design research

Answer 22

Turner et al. (2020)

Question 23

Turner et al. (2020)

Answer 23

Objectives: Interrupted time series (ITS) designs are frequently used in public health to examine whether an intervention or exposure has influenced health outcomes. Few reviews have been undertaken to examine the design characteristics, statistical methods, and completeness of reporting of published ITS studies.

Study Design and Setting: We used stratified random sampling to identify 200 ITS studies that evaluated public health interventions or exposures from PubMed (2013-2017). Study characteristics, details of statistical models and estimation methods used, effect metrics, and parameter estimates were extracted. From the 200 studies, 230 time series were examined.

Results: Common statistical methods used were linear regression (31%, 72/230) and autoregressive integrated moving average (19%, 43/230). In 17% (40/230) of the series, we could not determine the statistical method used. Autocorrelation was acknowledged in 63% (145/ 230) of the series. An estimate of the autocorrelation coefficient was given for only 1% of the series (3/230). Measures of precision were reported for 63% of effect measures (541/852).

Conclusion: Many aspects of the design, methods, analysis, and reporting of ITS studies can be improved, particularly description of the statistical methods and approaches to adjust for and estimate autocorrelation. More guidance on the conduct and reporting of ITS studies is needed to improve this study design.

Question 24

Time series design with control

Answer 24

see notes

Question 25

Time series design with control research

Answer 25

Zhang et al. (2020)

Question 26

Zhang et al. (2020)

Answer 26

Objective To discuss the study design and data analysis for three-phase interrupted time series (ITS) studies to evaluate the impact of health policy, systems, or environmental interventions. Simulation methods are used to conduct power and sample size calculation for these studies.

Methods We consider the design and analysis of three-phase ITS studies using a study funded by National Institutes of Health as an exemplar. The design and analysis of both one-arm and two-arm three-phase ITS studies are introduced.

Results A simulation-based approach, with ready-to-use computer programs, was developed to determine the power for two types of three-phase ITS studies. Simulations were conducted to estimate the power of segmented autoregressive (AR) error models when autocorrelation ranged from -0.9 to 0.9 with various effect sizes. The power increased as the sample size or the effect size increased. The power to detect the same effect sizes varied largely, depending on testing level change, trend changes, or both.

Conclusion This article provides a convenient tool for investigators to generate sample sizes to ensure sufficient statistical power when three-phase ITS study design is implemented.

Question 27

Impact of free access to leisure facilities and community outreach on inequalities in physical activity: a quasi-experimental study

Answer 27

Re:fresh programme introduced free access to leisure facilities in Blackburn and Darwen in July (50+), September 2008 (16-24) and then April 2009 (25-49)

5 full time health trainers offered around 700h 1-1 coaching per year

see notes

Offered in more deprived areas to reduce inequality

see notes

On average upward trajectory

Don’t know whether it represents new people or existing members

Question 28

advantages of time series design

Answer 28

Enables detection of whether programme effects LT or ST

Series of tests before intervention can eliminate need of control

Series of tests before can be used to project results which would be expected

Can be used if only one site to conduct eval

Can detect secular trends

Good external val

Kontopantelis et al. (2015)

• Interrupted time series analysis is arguably the “next best” approach for dealing with interventions when randomisation is not possible or clinical trial data are not available
• Although several assumptions need to be satisfied first, this quasi-experimental design can be useful in providing answers about population level interventions and effects

Question 29

disadvantages of time series design

Answer 29

Problem of confounding

Changes in instruments during series of measurements

Loss/change of cases

Changes in group composition

Kontopantelis et al. (2015)
- However, their implementation can be challenging, particularly for non-statisticians

Question 30

The effectiveness and cost-effectiveness of a complex community sport intervention to increase PA: an interrupted time-series design (Anokye et al., 2018)

Answer 30

Objectives
○ Effectiveness and cost-effectiveness analyses of 2-staged community sports interventions; taster sports sessions compared w/ portfolio of community sport sessions

Design
○ Quasi-exp using interrupted time series design

Setting
○ Community sports projects delivered by 8 lead partners in London

Ps
○ Inactive people aged 14+ (n=246)

Interventions
○ Community sports interventions delivered in 2 stages, 6-week programme of taster sport sessions (stage 1) and 6-week programme of portfolio of community sporting sessions delivered by trained coaches (stage 2)

Outcome measures

a. Change in days with >=30min self-reported vigorous intensity PA, moderate intensity PA, walking and sport
b. Change in subjective well-being and EQ5D5L quality-adjusted life-years (QALYs)

Methods
○ Interrupted time series analysis evaluated effectiveness of 2-staged sports programmes
○ Cost-effectiveness analysis compared stage 2 with stage 1 from providers perspective, reporting outcomes of incremental cost per QALY (2015/16 price year)
○ Uncertainty assessed using deterministic and probabilistic sensitivity analyses

Results
○ Counterfactual change at 21 days lower for vigorous, moderate PA and sport
○ Stage 2 increased walking
○ Counterfactual change as 21 days in well-being pos particularly for ‘happiness’
○ Stage 2 more expensive but increased QALYs
○ Cost per QALY for stage 2 £50000 and has 29% chance of being cost-effective (£30000 threshold)

Conclusion
○ Community-based sport interventions could increase PA among inactive people
- Less intensive sport sessions may be more effective and cost-effective

Question 31

The effectiveness and cost-effectiveness of a complex community sport intervention to increase PA: an interrupted time-series design (Anokye et al., 2018) research

Answer 31

Farmer et al. (2020)

Question 32

Farmer et al. (2020)

Answer 32

Girls are less active than boys throughout childhood and adolescence, with limited research focusing on female community sports-based programs. This study aims to assess the effectiveness of a multi-component, community sports-based intervention for increasing girl’s physical activity (PA) levels, fundamental movement skill (FMS) proficiency, and psychological wellbeing, as relative to a second treatment group (the traditionally delivered national comparative program), and a third control group. One hundred and twenty female-only participants (mean age = 10.75 ± 1.44 years), aged 8 to 12 years old from three Ladies Gaelic Football (LGF) community sports clubs (rural and suburban) were allocated to one of three conditions: (1) Intervention Group 1 (n = 43) received a novel, specifically tailored, research-informed Gaelic4Girls (G4G) intervention; (2) Intervention Group 2 (n = 44) used the traditionally delivered, national G4G program, as run by the Ladies Gaelic Football (LGF) Association of Ireland; and (3) Control Group 3 (n = 33) received no G4G intervention (group 1 or 2) conditions and were expected to carry out their usual LGF community sports activities. Primary outcome measurements (at both pre- and 10-week follow up) examining the effectiveness of the G4G intervention included (1) PA, (2) FMS and (3) Psychological correlates (enjoyment levels, self-efficacy, peer and parental support). Following a two (pre to post) by three (intervention group 1, intervention group 2, and control group 3) mixed-model ANOVA, it was highlighted that intervention group 1 significantly increased in PA (p= 0.003), FMS proficiency (p= 0.005) and several psychological correlates of PA (p≤ 0.005). The findings demonstrate that the 10-week, specifically tailored, research-informed G4G intervention is a feasible and efficacious program, leading to a positive effect on the physical and psychological wellbeing of pre-adolescent Irish girls, relative to the traditionally delivered national G4G comparative program and control group conditions

Question 33

Connecticut crackdown YouTube video

Answer 33

Connecticut crackdown on speeding

Effect on fatalities

see notes

Pre-test/posttest design O (X) O

Is it due to crackdown?

Change due to internal val threats?
○ History - event occurred between pre and post that accounts for change
§ Maybe rainfall low = safer roads
○ Maturation - LT trend, not treatment, responsible for change
§ Driving fatalities falling in general as drivers more experienced
○ Testing: DV may change as result of pretest
§ News of high fatality made drivers more careful
○ Regression to the mean - if variable is extreme of pre, tend to be closer to average on post
§ High fatality rate fluke and so later expect it to be lower

Types of interrupted time-series designs
Interrupted time-series design OOOOOOOOOOOO(X)OOOOOOOOOOOO

see notes

History - somewhat addressed

Maturation - somewhat

Testing - no

Regression to the mean - yes - looking at longer period of time - general trend

Interrupted time-series with comparison group design

OOOOOOOOOOOO(X)OOOOOOOOOOOO
OOOOOOOOOOOO OOOOOOOOOOOO

see notes

Similar states to Connecticut

History - somewhat

Maturation - yes

Testing - somewhat - other states might see similar news

Regression to the mean - yes

New threat:
○ Diffusion of X
- Maybe drivers in other states are becoming more cautious due to crackdown

Multiple interrupted time-series design

OOOO(X)OOOO(X)OOOO(X)OOO(X)OOOO

Multiple interrupted time-series with comparison group design

OOOO OOOO OOO OOOO

Question 34

non-exp study design

Answer 34

last resort

Question 35

Before and after (pre-post)

Answer 35

see notes

Question 36

Before and after (pre-post) research

Answer 36

Ferraro and Miranda (2014)

Question 37

Ferraro and Miranda (2014)

Answer 37

In the field of environmental policy, randomized evaluation designs are rare. Thus researchers typically rely on observational designs to evaluate program impacts. To assess the ability of observational designs to replicate the results of experimental designs, researchers use design-replication studies. In our design-replication study, we use data from a large-scale, randomized field experiment that tested the effectiveness of normbased messages designed to induce voluntary reductions in water use. We attempt to replicate the experimental results using a nonrandomized comparison group and statistical techniques to eliminate or mitigate observable and unobservable sources of bias. In a companion study, Ferraro and Miranda (2013a) replicate the experimental estimates by following best practices to select a non-experimental control group, by using a rich data set on observable characteristics that includes repeated pre- and post-treatment outcome measures, and by combining panel data methods and matching designs. We assess whether non-experimental designs continue to replicate the experimental benchmark when the data are far less rich, as is often the case in environmental policy evaluation. Trimming and inverse probability weighting and simple difference-in-differences designs perform poorly. Pre-processing the data by matching and then estimating the treatment effect with ordinary least squares (OLS) regression performs best, but a bootstrapping exercise suggests the performance can be sensitive to the sample (yet far less sensitive than OLS without pre-processing).

Question 38

Assessing the effectiveness of a naturally occurring population-level PA intervention for children (Smith et al. 2019)

Answer 38

free gym pass in children

Question 39

Study design

Answer 39

Aim
○ To assess impact of recreation access pass on grade 5 children’s PA levels

Design
○ Pre-post eval of popn-level community-based intervention - Grade 5 ACT-i-Pass programme

Methods
- All grade 5 children in participating schools offered free pass to use at G5AP recreational facilities in London, Ontario, a mid-sized Canadian city between Sep 2014-June 2015

see notes

Equiv to consort diagram

Decline things free - stigma around deprived neighbourhoods

Large loss to follow-up - risk of attrition bias

see notes

Small difference on total sample - but sig

Analysis only run on final sample - considerable attrition bias - people who finished much more active - intention to treat analysis needed - would have removed sig p value

No effect for boys and small sig effect for girls

Non-minority less effect compared to minority

Sig diff between those that lived in single-parent household

Selection bias between Ps who wanted to P

Question 40

Study design research

Answer 40

Jefferson and Demicheli (1999)

Question 41

Jefferson and Demicheli (1999)

Answer 41

Study objective—To examine the relation between experimental and nonexperimental study design in vaccinology.

Design—Assessment of each study design’s capability of testing four aspects of vaccine performance, namely immunogenicity (the capacity to stimulate the immune system), duration of immunity conferred, incidence and seriousness of side effects, and number of infections prevented by vaccination.

Setting—Experimental and nonexperimental studies on hepatitis B (HB) vaccines in the Cochrane Vaccines Field Database.

Results—Experimental and nonexperimental vaccine study designs are frequently complementary but some aspects of vaccine quality can only be assessed by one of the types of study. More work needs to be done on the relation between study quality and its significance in terms of effect size.

Question 42

advantages of Pre-test post-test non-experimental design

Answer 42

Relatively simple to implement

Controls for Ps prior knowledge/attitudes/skills intentions

Question 43

disadvantages of Pre-test post-test non-experimental design

Answer 43

Cannot account for non-programme influences on outcomes

Causal attribution not possible

Cannot detect small but imp changes

Cannot rule out secular trends - was there gentle increase in PA levels in Canada anyway?

Question 44

advantages and disadvantages of Pre-test post-test non-experimental design

Answer 44

Purpose Nonexperimental research, defined as any kind of quantitative or qualitative research that is not an experiment, is the predominate kind of research design used in the social sciences. How to unambiguously and correctly present the results of nonexperimental research, however, remains decidedly unclear and possibly detrimental to applied disciplines such as human resource development. To clarify issues about the accurate reporting and generalization of nonexperimental research results, this paper aims to present information about the relative strength of research designs, followed by the strengths and weaknesses of nonexperimental research. Further, some possible ways to more precisely report nonexperimental findings without using causal language are explored. Next, the researcher takes the position that the results of nonexperimental research can be used cautiously, yet appropriately, for making practice recommendations. Finally, some closing thoughts about nonexperimental research and the appropriate use of causal language are presented.
Design/methodology/approach A review of the extant social science literature was consulted to inform this paper.

Findings Nonexperimental research, when reported accurately, makes a tremendous contribution because it can be used for conducting research when experimentation is not feasible or desired. It can be used also to make tentative recommendations for practice.

Originality/value This article presents useful means to more accurately report nonexperimental findings through avoiding causal language. Ways to link nonexperimental results to making practice recommendations are explored

Question 45

Strengthening non-exp designs

Answer 45

Since no control confounding can be problem

By constructing plausibility argument and controlling for contextual and confounding factors, non-exp designs can be strengthened

Difficult due to amount of confounding going on

Question 46

Strengthening non-exp designs research

Answer 46

Johnson (2001)

Question 47

Johnson (2001)

Answer 47

A substantial proportion of quantitative educational research is non-experimental because many important variables of interest are not manipulable. Because nonexperimental research is an important methodology employed by many researchers, it is important to use a classification system of nonexperimental methods that is highly descriptive of what we do and also allows us to communicate effectively in an interdisciplinary research environment. In this paper, the present treatment of nonexperimental methods is reviewed and critiqued, and a new, two-dimensional classification of nonexperimental quantitative research is proposed. The first dimension is based on the primary “research objective” (i.e., description, prediction, and explanation), and the second dimension is called the “time” dimension (i.e., cross-sectional, longitudinal, and retrospective).

Question 48

ideal study design

Answer 48

Study popn randomly allocated to intervention and control groups to ensure both groups as alike as poss

Measurement of popn chars, inc outcomes, undertaken prior to intervention

Sufficient no. Ps to detect predicted effects (often small)

Intervention delivered as intended with intervention group

Measurement of both intervention and control groups after intervention using same measures in all randomised Ps

Measurement choice reliable and valid, capable of detecting change in behav

Analysis of observed diffs between groups using appropriate stat tests

Study popn representative of popn from which drawn
Both researchers and Ps should be blind to group allocated to

Question 49

Quasi experimental designs (YouTube)

Answer 49

To demo causal r’ship

No random assignment

Indv diff variable rather than IV - e.g. gender

Static group comparison design

Pretest-posttest nonequiv control group design

One-group pretest-posttest design

Interrupted time-series design

Replicated interrupted time-series design

Question 50

Static group comparison design

Answer 50

see notes

No random assignment

Selection threat to internal val

Makes causal direction more ambiguous

Question 51

Pretest-posttest nonequiv control group design

Answer 51

see notes

Determine pre-existing diffs in DV

Disambiguates causal order

Question 52

One-group pretest-posttest design

Answer 52

see notes