Experiments in social science Seeking causal explanations.

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Presentation transcript:

Experiments in social science Seeking causal explanations

Causality w Telecommunications managers, like social scientists, would like to be able to make causal statements--even if they only point to partial causality w “X causes Y” w Incomplete or imperfect causality Multiple causality Partial causality (increased likelihood) Necessary and sufficient conditions

Three conditions for establishing a causal relationship between two concepts 1. Covariation 2. Time order 3. Elimination of alternative explanations

Experiments w The experiment is a method where the researcher manipulates one variable (independent variable) and observes its effect on another (dependent variable) under controlled conditions

Experiments w Example: A researcher may expose a group of students to a movie with one ending and a second group to the same movie with a different ending (both under laboratory conditions), then measure their emotional response to the movie

Features of the experiment w Independent variable w Dependent variable w Subjects w Control

Independent variable w The independent variable is the ‘cause’ or ‘causal variable’ in the hypothesis to be tested w The researcher manipulates the independent variable and subsequently measures subjects on the dependent variable w A factor in an experiment is an independent variable whose levels are set by the experimenter

Independent variable w The levels of the factor that are introduced into the experiment are called the ‘treatments’ w If a group is measured on the dependent variable but is not exposed to a non-zero treatment, it is called a ‘control group’ Some consider this a zero-level treatment, others say it is not a treatment

Independent variable w The factor in an experiment must be represented by at least two treatments— experimental and control treatments or two experimental treatments w Stronger experiments include multiple treatment levels

w Examples: exposure to a video game v. non-exposure exposure to different executions of a creative idea having one half of a class use a website as part of the course and the other half not use it Exposing one group of subjects to one hour of rap music, another to two hours, another to three, and another to four hours

Dependent variable (effect) w The outcome of interest in the study w All groups are measured on the DV w Represents the ‘effect’ w Examples: liking for a show or a television personality recall of information from a website time spent at a website purchase of cell phones political activity

Subjects w People who are assigned to experimental conditions and measured on the dependent variable w They should be members of the target market/audience w They are often a ‘convenience sample’— especially students in lower-level psychology classes Nonrandom sampling

Control w Any procedures used to see that the only thing that varies for the subject groups is the independent variable The goal is to isolate impact of the independent variable on the dependent variable

Forms of control w Control of the environment Minimize distraction from noise, lights, action other than exposure to the independent variable Keep the environment the same across groups w Random assignment of subjects to treatments (randomization) Trying to make subject groups equivalent in terms of personalities, experiences, demographics

Forms of control (continued) w Identical presentation of treatment and measure of dependent variable among groups Placebo Timing w Statistical control Statistically remove the influence of demographics, prior experience, etc. Requires measuring all variables you will use as controls

Forms of control (cont’d) w Experimental Design Blocking

Basic experimental design RX O R O

Goal w The ultimate goal of the research is to determine whether the independent variable ‘causes’ the dependent variable under specified conditions w This sounds simpler than it is

Strengths of the experimental method w Strong claims to ‘internal’ validity w Strongest ability to infer causality w Relatively low cost w Straightforward interpretation w Scientific aura

Weaknesses of the experimental method w Troubles with ‘external’ validity Artificial setting Demand characteristics Hawthorne effect Forced exposure Multiple influences controlled Non-representative samples Measures divorced from concepts Kicking a Bobo doll