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Week 4 - Discussion 1

Quantitative Research Designs

A research design is like a blueprint for conducting research. It guides the researcher in determining when and how often the data will be collected, what data will be collected and from whom, and how the collected data will be analyzed. While there are several research designs available, the most common designs associated with quantitative research include true experiments, quasi- experiments, pre-experiments and correlations.

Instructions:

First, select one quasi-experimental design and develop an example of a study that would require that design. Identify the independent and dependent variables, and discuss the necessary conditions required for that design.

Then, answer the following questions:

· How could you change this study to make it a true experiment?

· What would be the advantages of using a true experimental design over a quasi-experimental design?

· In what situations might a quasi-experimental design be preferred over a true experimental design?

Your post should be at least 300 words

Resources

Required Text

Malec, T. & Newman, M. (2013). Research methods: Building a knowledge base. San Diego, CA: Bridgepoint Education, Inc. ISBN-13: 9781621785743, ISBN-10: 1621785742. Chapter 5: Experimental Designs – Determining Cause-and-Effect Relationships

Required References

Explorable (2010). Experimental research. Available at  https://explorable.com/experimental-research (Links to an external site.)

Onwuegbuzie, A. & Leech, N. L. (2005). On becoming a pragmatic researcher: The importance of combining quantitative and qualitative research methodologies. International Journal of Social Research Methodology, 8(5), 375-387. doi: 10.1080/13645570500402447

Svensson, C. (2014). Qualitative methodology in unfamiliar cultures: Relational and ethical aspects of fieldwork in Malaysia. London: SAGE Publications Ltd doi: 10.4135/978144627305014533923

Trochim, W. M. K. (2006). Research methods: Knowledge base. Available at  http://www.socialresearchmethods.net/kb/ (Links to an external site.)

Tsene, L. (2016). Qualitative multi-method research: Media social responsibility. London: SAGE Publications Ltd. doi: 10.4135/978144627305015595393

Key Components of Experimental Research Design

The Manipulation of Predictor Variables

In an experiment, the researcher manipulates the factor that is hypothesized to affect the outcome of interest. The factor that is being manipulated is typically referred to as the treatment or intervention. The researcher may manipulate whether research subjects receive a treatment (e.g., antidepressant medicine: yes or no) and the level of treatment (e.g., 50 mg, 75 mg, 100 mg, and 125 mg).

Suppose, for example, a group of researchers was interested in the causes of maternal employment. They might hypothesize that the provision of government-subsidized child care would promote such employment. They could then design an experiment in which some subjects would be provided the option of government-funded child care subsidies and others would not. The researchers might also manipulate the value of the child care subsidies in order to determine if higher subsidy values might result in different levels of maternal employment.

Random Assignment

· Study participants are randomly assigned to different treatment groups

· All participants have the same chance of being in a given condition

· Participants are assigned to either the group that receives the treatment, known as the "experimental group" or "treatment group," or to the group which does not receive the treatment, referred to as the "control group"

· Random assignment neutralizes factors other than the independent and dependent variables, making it possible to directly infer cause and effect

Random Sampling

Traditionally, experimental researchers have used convenience sampling to select study participants. However, as research methods have become more rigorous, and the problems with generalizing from a convenience sample to the larger population have become more apparent, experimental researchers are increasingly turning to random sampling. In experimental policy research studies, participants are often randomly selected from program administrative databases and randomly assigned to the control or treatment groups.

Validity of Results

The two types of validity of experiments are internal and external. It is often difficult to achieve both in social science research experiments.

Internal Validity

·  When an experiment is internally valid, we are certain that the independent variable (e.g., child care subsidies) caused the outcome of the study (e.g., maternal employment)

· When subjects are randomly assigned to treatment or control groups, we can assume that the independent variable caused the observed outcomes because the two groups should not have differed from one another at the start of the experiment

· For example, take the child care subsidy example above. Since research subjects were randomly assigned to the treatment (child care subsidies available) and control (no child care subsidies available) groups, the two groups should not have differed at the outset of the study. If, after the intervention, mothers in the treatment group were more likely to be working, we can assume that the availability of child care subsidies promoted maternal employment

One potential threat to internal validity in experiments occurs when participants either drop out of the study or refuse to participate in the study. If particular types of individuals drop out or refuse to participate more often than individuals with other characteristics, this is called differential attrition. For example, suppose an experiment was conducted to assess the effects of a new reading curriculum. If the new curriculum was so tough that many of the slowest readers dropped out of school, the school with the new curriculum would experience an increase in the average reading scores. The reason they experienced an increase in reading scores, however, is because the worst readers left the school, not because the new curriculum improved students' reading skills.

External Validity

·     External validity is also of particular concern in social science experiments

· It can be very difficult to generalize experimental results to groups that were not included in the study

· Studies that randomly select participants from the most diverse and representative populations are more likely to have external validity

· The use of random sampling techniques makes it easier to generalize the results of studies to other groups

For example, a research study shows that a new curriculum improved reading comprehension of third-grade children in California. To assess the study's external validity, you would ask whether this new curriculum would also be effective with third graders in New York or with children in other elementary grades.