EXPERIMENTAL DESIGNS PPT

EXPERIMENTAL DESIGNS- TYPES AND THEIR ANALYSIS TECHNIQUES

1. RESEARCH METHODOLOGY EXPERIMENTAL DESIGNS- TYPES AND THEIR ANALYSIS TECHNIQUES NIVEDITA MENON. C 06/03/2021

2. EXPERIMENTAL DESIGNS Experimental design means creating a set of procedures to test a hypothesis. A good experimental design requires a strong understanding of the system you are studying. By first considering the variables and how they are related (Step 1) , you can make predictions that are specific and testable (Step 2) .

3. How widely and finely you vary your independent variable (Step 3) will determine the level of detail and the external validity of your results. Your decisions about randomization, experimental controls, and independent vs repeated-measures designs (Step 4) will determine the internal validity of your experiment.

4. TYPES OF DESIGNS

5. TRUE EXPERIMENTS In general, designs considered to be true experiments contain three basic key features: 1. random assignment of participants into experimental and control groups 2. a treatment (or intervention) provided to the experimental group 3. measurement of the effects of the treatment in a post-test administered to both groups. Some true experiments are more complex. Their designs can also include a pre-test and can have more than two groups, but these are the minimum requirements for a design to be a true experiment.

6. 1. Experimental and Control Groups the effect of an intervention is tested by comparing two groups: one that is exposed to the intervention; the experimental group, also known as the treatment group and another that does not receive the intervention; the control group. Importantly, participants in a true experiment need to be randomly assigned to either the control or experimental groups. 2. Treatment or Intervention In an experiment, the independent variable is receiving the intervention being tested. In some cases, it may be immoral to withhold treatment completely from a control group within an experiment.

7. For these cases, researchers use a control group that receives “treatment as usual”. Experimenters must clearly define what treatment as usual means. A substance abuse researcher conducting an experiment may use twelve-step programs in their control group and use their experimental intervention in the experimental group. The results would show whether the experimental intervention worked better than normal treatment, which is useful information. 3. Post-Test The dependent variable is usually the intended effect the researcher wants the intervention to have. Thus, the researcher must at a minimum, measure the number of episodes that occur after the intervention, which is the post-test. In a classic experimental design, participants are also given a pretest to measure the dependent variable before the experimental treatment begins.

8. QUASI-EXPERIMENTAL DESIGNS Quasi-experimental designs are similar to true experiments, but they lack random assignment to experimental and control groups. Quasi-experimental designs have a comparison group that is similar to a control group except assignment to the comparison group is not determined by random assignment. While this method is more convenient for real-world research, it is less likely that that the groups are comparable than if they had been determined by random assignment.

9. Quasi-experiments are particularly useful in social welfare policy research. Non equivalent comparison group design are as follows: 1. Natural Experiments Social welfare policy researchers often look for what are termed natural experiments or situations in which comparable groups are created by differences that already occur in the real world. Natural experiments are a feature of the social world that allows researchers to use the logic of experimental design to investigate the connection between variables. 2. Matching It begins with researchers thinking about what variables are important in their study, particularly demographic variables or attributes that might impact their dependent variable.

10. Individual matching involves pairing participants with similar attributes. Then, the matched pair is split—with one participant going to the experimental group and the other to the comparison group . Researchers may engage in aggregate matching , in which the comparison group is determined to be similar on important variables. 1. The Time Series Design The time series design uses multiple observations before and after an intervention. In some cases, experimental and comparison groups are used. In other cases where that is not feasible, a single experimental group is used. By using multiple observations before and after the intervention, the researcher can better understand the true value of the dependent variable in each participant before the intervention starts. Additionally, multiple observations afterwards allow the researcher to see whether the intervention had lasting effects on participants.

11. PRE-EXPERIMENTAL DESIGN Pre-experimental designs are called such because they often happen as a pre-cursor to conducting a true experiment. Researchers want to see if their interventions will have some effect on a small group of people before they seek funding and dedicate time to conduct a true experiment. Pre-experimental designs, thus, are usually conducted as a first step towards establishing the evidence for or against an intervention. 1. One-group Pre-test Post-test Design Pre- and post- tests are both administered, but there is no comparison group to which to compare the experimental group.

12. Researchers may be able to make the claim that participants receiving the treatment experienced a change in the dependent variable, but they cannot begin to claim that the change was the result of the treatment without a comparison group.

13. EX POST FACTO RESEARCH DESIGN An ex post facto research design is a method in which groups with qualities that already exist are compared on some dependent variable. Also known as "after the fact" research, an ex post facto design is often considered quasi-experimental because the subjects are not randomly assigned - they are grouped based on a particular characteristic or trait. Although differing groups are analyzed and compared in regards to independent and dependent variables it is not a true experiment because it lacks random assignment. The assignment of subjects to different groups is based on whichever variable is of interest to the researchers.