2: Types of Studies 1

Chapter 2: Chapter 2: Types of StudiesTypes of Studies

2: Types of Studies 2

In Chapter 2:

2.1 Surveys

2.2 Comparative Studies

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Types of Studies• SurveysSurveys: describe population characteristics

§2.1

• Comparative studies:Comparative studies: determine relationships between variables §2.2

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2.1 Surveys• Goal: describe population characteristics

• Normally based on a sample (or subset) of the population

• Types of samples– Probability sample (e.g., simple random

sample)– Non-probability sample (e.g., convenience

sample)

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Sampling• Probability samples use chance

mechanisms to select individuals

• The most basic type of probability sample is the simple random sample (SRS)

• SRS ≡ a sample of size n selected so that all possible combinations of n individuals from the population are equally likely to comprise the sample

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SRS Method1. Identify each population member with the

numbers 1, 2, . . ., N

2. Pick a random spot to enter Table A3. Select n tuples, discarding inappropriate tuples

Alternatively, use a random number generator (e.g., www.random.org) to generate n random numbers between 1 and N

Keep in mind: the objective of an SRS: every possible subset is equally likely!

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Other Types of Probability Samples (More Advanced Methods)

• Stratified random sample: randomly sample strata (subsets) with the population

• Cluster sample: randomly sample clusters comprising varying numbers of observations

• Multistage sampling: randomly sample random samples in multiple stages

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Cautions Undercoverage: groups in the source

population are left out or underrepresented sampling frame

Volunteer bias: self-selected participants (volunteers) are atypical population members

Nonresponse bias: a large percentage of individuals refuse to participate or cannot be contacted

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§2.2 Comparative Studies

• Objective: to determine the relationship between an explanatory and response variable

• Experimental designs assign subjects to treatment or exposure groups and compare outcomes

• Nonexperimental design classified subjects in exposure groups (no intervention) and compare outcomes

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Study Design Outlines

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Women’s Health Initiative (WHI) Experimental Design

The WHI study randomly assigned about half its subjects to a group that received hormone replacement therapy (HRT). The other half received an identical looking placebo.

Subjects were followed for ~5 years to ascertain various health outcomes, including heart attacks, strokes, breast cancer and so on.Example of publication: Writing Group for the Women's Health Initiative Investigators. (2002). Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the Women's Health Initiative randomized controlled trial. JAMA, 288(3), 321-333.

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Nurse’s Health Study (NHS) Nonexperimental Design

This study classified individuals according to whether they received HRT

Subjects were followed (ongoing) for various health outcomes, e.g., heart attacks, strokes, breast cancer and so on.

Example of publication: Stampfer, M., Colditz, G., Willett, W., Manson, J., Rosner, B., Speizer, F., et al. (1991). Postmenopausal estrogen therapy and cardiovascular disease. Ten-year follow-up from the nurses' health study. New England Journal of Medicine, 325(11), 756-762.

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Comparison of WHI and NHS

• Both the WHI and NHS analyzed relationships between HRT (explanatory variable) and various health outcomes (response variables)

• WHI investigators assigned the exposure (HRT) experimental

• NHS investigators measured the exposure but did not assign it nonexperimental (observational)

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Let us focus on selected experimental design concepts

and techniquesExperimental designs provides a

paradigm for nonexperimental designs.

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Terminology Used in Experiments

• Subject ≡ an individual participating in the experiment

• Factor ≡ an explanatory variable being studied in an experiment

• Treatment ≡ a specific set of factors

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Subjects, Factors, Treatments (Illustration)

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• Subjects = 100 individuals who participated in the study• Factor A = Health education (active, passive)• Factor B = Medication (Rx A, Rx B, or placebo)• Treatments = the six specific combinations of factor A

and factor B

Subjects, Factors, Treatments, Example, cont.

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Schematic Outline of Study Design

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Randomized Controlled Trials (RCT)

• Randomized: chance assigns the exposure

• Controlled: the exposed group is compared to a non-exposed group (comparative study design)

• Blinded: observations are made without knowledge subjects’ exposure status

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Randomization• Randomization is the second principle of

experimentation• Randomization refers to the use of chance

mechanisms to assign exposures / treatments

• Randomization balances lurking variables among comparison groups, mitigating confounding effects of lurking variables

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Randomization - ExampleSource: JAMA 1994;271:595-600 (link is active)• Explanatory variable: Nicotine or placebo patch• 60 subjects (30 in each group)• Response variable / outcome: Cessation of

smoking (yes/no)

Random Assignment

Group 130 smokers

Treatment 1 Nicotine Patch

CompareCessation

ratesGroup 2

30 smokers

Treatment 2 Placebo Patch

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Randomization – Example

• Number subjects 01,…,60

• Use Table A (or a random number generator) to select 30 two-tuples between 01 and 60

• If you use Table A, arbitrarily select a different starting point each time

• For example, if we start in line 19, we see 04247 38798 73286

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Randomization, cont.

• We identify random two-tuples, e.g., 04, 24, 73, 87, etc.

• Random two-tuples greater than 60 are ignored• The first three individuals in the treatment group are

01, 24, and 29• Keep selecting random two-tuples until you identify

30 unique individuals • The remaining subjects are assigned to the control

group

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Controlled Trial

• “Controlled” means there is non-exposed control group

• A concurrent control group is essential • You cannot judge the effects of an expose

without a concurrent control group because:– Many factors contribute to a health outcome

(so-called multi-causality; causal interdependence)

– Conditions change on their own over time– The placebo (and related) effects

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Blinding• Blinding: the measurement of the response

made without knowledge of treatment type• Works by balancing measurement error and

preventing observer bias• Can occur at several levels:

– Single blinding: subjects blinded– Double blinding: subjects and measurement-

takers blinded– Triple blinding: subjects, measurement-takers,

analysts blinded

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Ethics of Experimental Studies

• Equipoise - balanced doubt; can’t knowingly expose subjects to harm or withhold benefit

• Informed consent – subjects must be aware of study objectives

• Beneficence – must provide overall benefit to society

• Justice – must be administrated justly• Independent oversight (e.g., IRB)