• Charecteristics and Types
• Internal and External Validity
• True experimental designs
• Quasi experimental designs
• Evaluative and other designs
• References

INTRODUCTION

• Brink and Wood presents three basic levels of design- experimental, survey and exploratory-descriptive, each of which contains two sub levels namely experimental designs: experimental and quasi-experimental; Survey designs: comparative and correlational; exploratory-descriptive designs: descriptive and exploratory.

• Ideally, at successively higher levels of design, the degree of control and the level of knowledge about the variables increases.

• The level of knowledge about pertinent variables should be the greatest at the level of the experiment and is expected to be most limited at the exploratory level.

• The choice of the appropriate design is based on the current level of knowledge about the research topic. The current level of knowledge and theory about a topic must be thoroughly examined prior to entering into an experimental design.

• Two methods of examining existing theory on any well studied topic is either to do a conceptual mapping of the literature to determine what is missing, what is conflicting and what is causal or to perform meta analysis of the published literature to determine if there are conclusions that can be drawn and applied or whether further work is needed to explain contradictions or omissions.

• When a causal relationship between variables can be both predicted and ethically tested, experimental or quasi experimental designs are warranted.

• Experiments  broadly defined are tests that involve at least one treatment (independent variable), units (subjects) to be analyzed by assignment  or non assignment to a treatment and a comparison for inferring effects that may be attributed to the treatment.

CHARECTERISTICS OF EXPERIMENTAL DESIGNS

To test a relationship and most confidently infer this result, experimental designs must be characterized by three essential elements: randomization, manipulation and control.

A. Randomization

Randomization refers to participants being assigned by chance to either receive or not receive the treatment condition or intervention. A number of procedures exist for assigning individuals to groups such as coin toss, a random numbers table or computerized random number generators. The key characteristic of all these procedures is that each participant has an equal and known probability of being assigned to either the control or the experimental group. 

Randomization helps eliminate bias by spreading variability due to extraneous variables equally across the groups under study. The advantage of assigning participants to groups in a random manner is that this should result in the group’s initially being similar to one another prior to the intervention. Random assignment to condition does not guarantee that the two groups will be similar to one another. Based on sampling theory, significant difference(p<0.05) between the two groups will occur in 1:20 cases of assigning participants to groups. The sample size should be large enough or else researcher may wish to consider some additional methods of distributing important variables such as matching or use of more homogeneous population. In some research, it is necessary to randomly assign treatment conditions, to units other than the individual participants. Randomization may be cluster, stratified, fixed or by random assignment.

B. Manipulation:

Manipulation is the process of maneuvering the independent variable so that its effect on the dependent variable can be observed. The causative variable must be amenable to manipulation by the investigator, i.e. the researcher does something to subjects in the experimental condition.  It is essential that researchers conduct manipulation checks to see whether the manipulation had its intended effect or perhaps resulted in an unintended effect that could compromise the validity of an experiment. In working to avoid unintended effects researchers should be cautious of the use of reactive measures which can influence participants’ responses to the dependent variable. Even though researcher does not actively manipulate the control group, it is important that he or she be aware of what may be happening to them Control group should experience all the same things as participants in the experimental group, except the independent variable.  Ethical considerations, organizational policy or some variables like attitudes, age, disease etc which cannot be manipulated may disallow manipulation. The ability of the researcher to manipulate the independent variable is a major source of control in experimental studies.

C. Control

Cook and Campbell identify three uses of the term control in relation to research designs, all of which involve elimination of threats to valid inference namely the researchers control over the research environment; control over the experimental variable; the ability to identify and rule out threats to internal validity. The last type of control is typically achieved through the use of a comparison or control group and through attention to sources of variance.  In many nursing studies control groups receive the usual or traditional methods of care rather than no treatment against which effects of the experimental intervention are measured.

Kerlinger discusses the merits of experimental designs in terms of their ability to control variance or to take into account factors that may contribute to differences in the dependent variable. To provide valid  answers to research questions, three kinds of variance must be considered: systematic or experimental variance which refers to the systematic effect of independent variable on the dependent variable and is a type of variance which should be enhanced; extraneous variance which refers to the effects of extraneous variables on the dependent variables, which is to be controlled by the design by building the extraneous variable into the design as an independent variable, eliminating or holding constant an extraneous variable by selecting participants as homogeneous as possible on that variable, matching participants and using statistical control; error variance which refers to the variability of measures due to random fluctuations including errors of measurement, which can be controlled by standardizing the instrument/ measurement conditions (keeping the time of the day, place instructions, personnel constant) or using sensitive, reliable instruments. Internal validity is the primary objective of experimental methodology

TYPES OF EXPERIMENTAL DESIGNS

There are of two major types of experimental designs, true experiments and quasi experiments. True experiments include the random assignment of units to comparison groups for inferring a change that has been caused by treatment. Random assignment is an essential component of true experiments that is designed to achieve comparability of comparison groups.

Quasi experiments have a treatment, outcomes and units to be analyzed, but random assignment of units to comparison groups is not included for determining the groups of units to be compared. An important assumption underlying all true experimental designs is that equivalence of groups is maintained throughout the course of the experiment and is not compromised by things such as differential attritions – i.e. variable dropout rates may make experimental and control subjects different on critical factors at the time of the analysis. If experimental and control groups become nonequivalent, the design then becomes quasi experimental.