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There are many types of quantitative research designs, generally there are two umbrellas: experimental and non-experimental research.

Experimental Research

Cause and effect must be defined terms of necessary and sufficient conditions. For example, if the condition is necessary and sufficient to produce the effect, then it is the cause. Alternative situations exist as well:

1. Necessary but not sufficient meaning some related condition likely produces the effect.

2. Sufficient but necessary meaning some alternative condition is likely the cause.

3. Neither necessary nor sufficient meaning some contributing condition is likely the cause.

Experimental research is commonly used in sciences such as sociology, psychology, physics, chemistry, biology and medicine. There are three basic types: pre-experimental designs, true experimental designs and quasi-experimental designs.

An example of experimental would be if a researcher is conducting a study of efficacy of chlorhexidine mouth wash on prevention of ventilator-associated pneumonia among patients admitted to ICU. The chlorhexidine mouthwash is the dependent variable, which is manipulated by the researcher and is used as an intervention for the experimental group, while the control group is kept deprived of it to observe it effect on the incidence of VAP.

Nonexperimental Research

It’s one of the broad categories of research designs, in which the research observes the phenomena as they occur naturally, and no external variables are introduced. It’s designed in which variables are not deliberately manipulated, nor is the setting controlled. Researcher collected data without making changes or introducing treatments. Types of nonexperimental research includes:

Descriptive Correlation Developmental Epidemiological Survey Research

Health and human services are the three most common types of nonexperimental research which includes surveys, passive observation and export factor designs.

Experimental vs Nonexperimental

Experimental researchers manipulate or controls variables and observes effect in other variables. They evaluate cause and effect relationships, for example does the pre-op interventions program improve self-efficacy post op?

Nonexperimental describes or looks at relationships or correlation between variables. The variables are not manipulated by the observer. For example, the observe the correlations between the patient’s heart rate and breast cancer. Nothing is changes or manipulated, data is collected as is to make an analysis.