More Research Design

Andrew MartinPS 372

University of Kentucky

Large-N vs. Small-N

Often political scientists talk in terms of large-n and small-n when referring to the number of observations in a study.

N is the mathematical operator that designates the number of observations in a sample.

Large-N studies tend to be experimental, cross-sectional and quasi-experimental research designs, and small-n tend to be pre-experimental or qualitative.

Small-N Design

In small-N design the researcher examines one or a few cases of a phenomenon in considerable detail, typically using several data collection methods such as interviews, document analysis and observation.

This research is also known as qualitative or pre-experimental research.

Such research has weak external and internal validity and does not allow researchers to make causal inferences.

Mill's Method of Difference

John Stuart Mill suggested examining cases where the phenomenon under investigation occurs and does not occur.

Within these instances, examine the similarities and differences for each variable in the theory.

If only one key difference exists between the two observations and the theorized antecedent variables, the scholar has identified the “cause.”

Mill's Method of Difference

Pre-Experimental Design

Pro: Allows researchers to gather information when no other research design can be applied, or may allow researchers to show that further, more valid, research would be valuable.

Con: Weak internal and external validity, inability to make causal inferences.

Cross-Sectional Design

Cross-sectional design allows measurements of the independent and dependent variables to be taken at the same time.

The researcher cannot control or manipulate: 1. the independent variable 2. the assignment of subjects to groups 3. the conditions under which the independent variable is experienced

Cross-Sectional Design

Cross-sectional studies frequently make use of survey or polling data when the unit of analysis is the individual.

When the unit of analysis is a grouping of units, such as countries or ethnic groups, other aggregate-level measures are employed.

Cross-Sectional Design

NN 117

Cross-Sectional Design

JRM 156-157

Cross-Sectional Design

Cross-Sectional Design

Because cross-sectional design do not allow for the same level of control as experiments, they often have weaker internal validity.

Conversely, because they allow researchers to carry out studies in real-life settings, they typically have more external validity than experiments.

Cross-sectional studies do not account for time. Because humans and their social environment are not static, but dynamic, this potentially poses problems.

Quasi-Experimental Designs

Similar to cross-sectional design in that they do not require individual assignment of cases to comparison groups.

They are superior to cross-sectional exams because they typically involve the study of more than one sample over an extended period of time.

Quasi-experimental exams can model changes in the level of variables or conditions over time. This can clarify the causal order (i.e. that X comes before Y).

Panel Studies

Panel studies examine the same sample at two or more time intervals.

Panel designs allow researchers to determine the direction or causation.

Panel Studies

NN 121

Panel Studies

NN 122

Panel Studies

JRm 161

Panel Design -- Problems

It is difficult to obtain and retain the same representative sample of respondents over an extended period of time.

Another potential problem is panel conditioning, where interviewers may condition respondents to give a particular a certain set of answers over time.

Time Series Models

When no comparison or control group is available for assessing cause-and-effect relations, time-series models are used.

In time-series studies, researchers typically try to obtain at least three measures both before and after the introduction of the independent variable. (Intervention Analysis in JRM)

Republican Party ascension in the United States

JRM 161

Republican Party ascension in the United States

JRM 161

ReaganPresidency

Time-series with control group design

Some studies combine the components of a panel and time-series design to create a time-series study that contains a control group.

Time-series with control group design

JRM 166

Formal Models

Formal models are a simplified and abstract representation of reality that can be expressed verbally, mathematically or in some other symbolic system, and purports to show how variables or parts of a system tie together.

Formal Models

The main parts of a formal model are:

(1) a set of primitives, or undefined terms whose meaning is taken for granted

(2) a collection of assumptions(3) a body of rules or logic for linking the parts of

the model together(4) various derived propositions that are true by

virtue of the rules used to deduce them

JRM 171

Simulations

Simulations are simple representations of a system by a device in order to study its behavior.

JRM 174