Question

• Define each type of variable: dichotomous, ordinal, categorical, continuous • Define the following study designs: Randomized controlled trial, prospective cohort study, case-control study, crossover study. • Define in dependent versus independent samples.

Answer 1

a) Define each type of variable

1) dichotomous: A dichotomous variable is one that takes on one of only two possible values when observed or measured. The value is most often a representation for a measured variable (e.g., age: under 65/65 and over) or an attribute (e.g., gender: male/female).

2) ordinal: An ordinal variable is a categorical variable for which the possible values are ordered. Ordinal variables can be considered “in between” categorical and quantitative variables.

Example: Educational level might be categorized as
    1: Elementary school education
    2: High school graduate
    3: Some college
    4: College graduate
    5: Graduate degree

3) categorical: a categorical variable is a variable that can take on one of a limited, and usually fixed number of possible values, assigning each individual or other unit of observation to a particular group or nominal category on the basis of some qualitative property.^[1] In computer science and some branches of mathematics, categorical variables are referred to as enumerations or enumerated types. Commonly (though not in this article), each of the possible values of a categorical variable is referred to as a level. The probability distribution associated with a random categorical variable is called a categorical distribution.

4) continuous: Continuous Variable. If a variable can take on any value between its minimum value and its maximum value, it is called a continuous variable

b) Define the following study designs

1) Randomized controlled trial: A randomized controlled trial (or randomized control trial;^[2]RCT) is a type of scientific (often medical) experiment that aims to reduce certain sources of bias when testing the effectiveness of new treatments; this is accomplished by randomly allocating subjects to two or more groups, treating them differently, and then comparing them with respect to a measured response. One group—the experimental group—has the intervention being assessed, while the other—usually called the control group—has an alternative condition, such as a placebo or no intervention. The groups are followed under conditions of the trial design to see how effective the experimental intervention was.^[3] Treatment efficacy is assessed in comparison to the control. There may be more than one treatment group or more than one control group.

2) prospective cohort study: A prospective cohort study is a longitudinal cohort study that follows over time a group of similar individuals (cohorts) who differ with respect to certain factors under study, to determine how these factors affect rates of a certain outcome.^[1] For example, one might follow a cohort of middle-aged truck drivers who vary in terms of smoking habits, to test the hypothesis that the 20-year incidence rate of lung cancer will be highest among heavy smokers, followed by moderate smokers, and then nonsmokers.

3) case-control study:

Case-control studies

Case-control studies are retrospective. They clearly define two groups at the start: one with the outcome/disease and one without the outcome/disease. They look back to assess whether there is a statistically significant difference in the rates of exposure to a defined risk factor between the groups. See Figure 1 for a pictorial representation of a case-control study design. This can suggest associations between the risk factor and development of the disease in question, although no definitive causality can be drawn. The main outcome measure in case-control studies is odds ratio (OR).

4) crossover study:

In medicine, a crossover study or crossover trial is a longitudinal study in which subjects receive a sequence of different treatments (or exposures). While crossover studies can be observational studies, many important crossover studies are controlled experiments, which are discussed in this article. Crossover designs are common for experiments in many scientific disciplines, for example psychology, pharmaceutical science, and medicine.

c) Define in dependent versus independent samples

Independent samples are samples that are selected randomly so that its observations do not depend on the values other observations. Many statistical analyses are based on the assumption that samples are independent. Others are designed to assess samples that are not independent.

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