Quantitative Design Descriptive, Correlational and Comparative.

Quantitative Design

Descriptive, Correlational and Comparative

Session Objectives

Choosing the correct quantitative methodology

A History of quantitative research

What type of research should I be doing?

Descriptive research

Correlational research

Experimental research

Related and unrelated designs

Randomisation and controls

Blinding / ITT / Time periods

Involve

“We believe that involving members of the public leads to research that is:

• more relevant to people’s needs and concerns • more reliable • more likely to be used”

http://www.invo.org.uk

http://www.invo.org.uk/

Session Objectives










A History of Quantitative Reasoning

• Positivism

• Empiricism

• Deduction and Induction

• Hypothetico-deductive model

Reject / modify theory

Falsification

Deduction

Test Hypothesis

Hypothesise

Generalise

Describe

Measure

Observe

Session Objectives










Am I…

• Using numbers from outcomes

• Comparing the effectiveness of two treatments

• Determining relationships between two variables

• Monitoring the progress of a group of patients

• Using text / pictures / objects

• Seeking opinions

• Observing human behaviour (immersing myself)

• Exploring subjective meanings / phenomena

Quantitative Research Qualitative Research

Then I’m doing…

Session Objectives










Choosing the correct research method

Alternatives:-

• Descriptive studies

• Correlation studies

• Experimental studies

Allocate the research method to these studies

• Do patients with greater ventilatory defects experience more fatigue after stroke?

• How many patients with stroke suffer from fatigue?

• Do interventions to increase ventilatory capacity reduce fatigue?

• What is the size of the ventilatory defect after stroke?

Session Objectives










Descriptive studies

• Clear, specific, measurable definition of the disease/condition

• Least-publishable medical literature

• Feedback to those who need to know

• Important for:• Trend analysis• Healthcare planning• Hypothesis generation

• Do not over analyse!

NICE levels of evidence

Level Type of evidence

Ia: Evidence from meta-analysis of randomised controlled trials Ib: Evidence from at least one randomised controlled trialIIa: Evidence from at least one controlled study without

randomisationIIb: Evidence from at least one other type of quasi-experimental

study III: Evidence from non-experimental descriptive studies, such as

comparative studies, correlation studies and case-control studies

IV: Evidence from expert committee reports or opinions and/or clinical experience of respected authorities

Session Objectives











• Investigate the relationship between variables

• Use one randomly selected group

• Use two variables – both measurable (interval level)

• It does not tell us the cause of the relationship

Correlation studies

0

2

4

6

8

10

0 2 4 6 8 10A

B

0

2

4

6

8

10

0 2 4 6 8 10A

B

Relationship between A and B

Positive correlation (1.0) Negative correlation (-1.0)

Session Objectives










The “classic experimental design”

Must include:

• 2 or more differently treated groups (treatment & control)

• Random allocation (chance assignment)

If design does not satisfy both of the above it is described as Quasi-experimental

An experiment

• Controlled conditions• Monitor an ‘effect’• Manipulation of an experimental variable• Experimental group• Control group• Minimisation of:

• Systematic errors (bias)• Random errors (chance)

• Independent variable

Session Objectives










Experimental Design

Terminology:– Related / within / same subject design

Types:

– Within subject studies

– Participants as own control

Within subject studiesUsing different limb as a control

Examples:• Injured vs. uninjured limb• Left vs. right• Dominant vs. non-dominant

measure Intervention measure

Treatment phase (B)

Participants as own controlUsing same limb as control

measure measure measure

Control phase (A) Treatment phase (B)

measure measure measure

A B

measure

A

Draw a flow chart for the following related-subject

studies:

1. Will the single-leg vertical hop test determine differences between lower limb dominance?

2. Validity of the 6 minute walk test for assessing HR recovery after an exercise-based cardiac rehabilitation programme

Experimental DesignTerminology:

– Unrelated / between / different-subject design

Types:– Matched design

– Crossover design

– Factorial design

– RCT

Matched designs

• 2 or more groups• Subject matched on ‘x’ variable(s)• May or may not be randomised to groups

Disadvantages• Can only match a few variables at a time• May miss more important variables• Has implications for analysis – unrelated

independent tests

Crossover design

Control

Treatment Treatment

ControlGroup 1

Group 2

Measure Measure Measure

Factorial design

ResistanceA

ge

>40

<40

Group 3Group 3 Group 4Group 4

Group 2Group 2Group 1Group 1

180/sec 320/sec

Factors: major independent variables

Factor subgroups

2X2 design

Draw a flow chart for the following unrelated-subject

studies

• Is the production of sputum dependent on type or duration of exercise in patients with cystic fibrosis?

• The effects of an early or delayed strengthening regime following ACL reconstruction surgery

• Quadriceps muscle strength is different for Asian, Caucasian and African-Caribbean children

Session Objectives










The randomised controlled trial

• Random allocation

• Similar groups

• Double blind

• Control group

• Numerical outcomes

• Intention to treat (ITT)

• Standardised procedures

Random allocation

• Unrestricted allocation• Tossing a coin• Random number tables

• Stratified randomisation

• Cluster randomisation

• Block randomisation

Allocation to groups – other methods

• Alternative

• Matching – max 3 variables

• Specification – similar to matching

• Minimisation

Controls

• Place the following in the order of importance

(1 = true experimental)

• Literature • No treatment• Placebo• Standard treatment• Historical• Own control

Session Objectives










Blinding

• Double blind• Therapist and / or researcher• Participant

• Single blind • Therapist and / or researcher

Very difficult to double blind in clinical research

Intention to treat (ITT)

• Sample attrition• Death• Dropout• Missing data

• Refusal to be randomised

ITT = Unbiased comparison of randomised groups regardless of the intervention

Time periods of study

• Cross sectional• Measurement taken at one point in time

• Prospective • longitudinal

• Retrospective• Historical

Advantages of experimental design

• Randomisation minimises the risk of extraneous variables confounding results

• Control over the independent variable allows clear understanding of cause and effect

• Pre- and post-testing controls for time-related threats to validity

• Allows for powerful statistical manipulation

• Will reveal causal relationships

Disadvantages of experimental design

• Difficult to represent specified population

• Difficult to choose control

• Difficult to control extraneous variables

• Natural environment not always achievable

• Patient adopts unnatural role

• Design lacks diversity of e.g. MDT roles

Quantitative Design Descriptive, Correlational and Comparative.

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