Chapter 4: Designing Studies

Flashcards on Designing Studies

Sample

A subset of population

Population

The entire group

Census

Data collected from the entire population

Convenience Sampling

Sampling from a group that is “close at hand”

Voluntary response sampling

People choose to join the sample

Simple Random Sample (SRS)

SRS of size n is chosen in a such way that every possible group of n individuals in the population has an equal chance of being selected

Stratified Random Sampling

Dividing the population into non-overlapping groups (strata), sampling from each of these groups and combining these “subsamples” to form the overall sample

Cluster

Group of individuals in the population that are located near each other

Cluster Sampling

Selects a sample by randomly choosing clusters and including each member of the selected clusters in the sample

Systematic Random Sampling

Selects a sample from an ordered arrangement of the population by random selecting one of the first k individuals and choosing every kth individual after.

Undercoverage

Occurs when some members of the population are less likely to be chosen or cannot be chosen in the sample

Nonresponse

Occurs when an individual chosen for the sample can’t be contacted or refuses to participate

Response Bias

Occurs when there is a systematic pattern of inaccurate answers to a survey question

Observational Study

Observe individuals and measures variables of interest but does not attempt to influence the responses

Response variable

Measures an outcome of a study

Explanatory variable

Help explain or predict changes in a response variable

Confounding

Variable that is associated with BOTH the explanatory variable and the response variable and may distort on confuse the true relationship between them

Experiment

Deliberately imposes treatments on individuals to measure their responses

Placebo

Treatment with no active ingredient, but is otherwise like the other treatments

Treatment

Conditions applied to individuals in an experiment

Experimental unit

Object to which treatment is randomly assigned

Subjects

Experiment unit = human

Factors

Different explanatory variables that are being manipulated, what’s being tested?

Levels

Specific value or category of a factor, change the factor change the level

Control group

Baseline for comparing the effects of other treatments.

Placebo Effect

Subjects will respond to the treatment even if it’s an inactive ingredient

Double-blind

Subjects + providers don’t know which treatment a subject is receiving

Single-blind

Either subjects or people interacting with them don’t know which the subject is receiving

Random Assignment

Experimental units are assigned to treatment using chance process

Replication

Using enough units/subjects os the effect of the treatments can be distinguished from chance differences

Completely randomized design

Experimental units are assigned to the treatments completely at random

Block

Group of experimental units that are known before the experiment to be similar in some way that is expected to affect the response to the treatments

Randomized Block Design

Random assignment of experimental units to treatment is carried out separately within each block.

Matched Pairs Design

Common experimental design for comparing two treatments that uses blocks of size 2. In some matched pairs designs, two very similar experimental units are paired and two treatments are randomly assigned within each pair. In other, each experimental unit receives both treatments in a random order.