Types of quantitative research methods and designs (2023)

Each doctoral student has his own reasons for obtaining a terminal diploma. Some are motivated by better career prospects, while others like the idea of ​​being recognized as experts in their field or have a passion for imparting new knowledge to leaders. Regardless of one's own motives for obtaining adoctorate, you are sure to develop stronger critical thinking and analytical reasoning along the way. This is mainly due to its strategic research design.

As you prepare for your dissertation quantitative research, you will need to think about structuring your research design. There are several types of quantitative research designs, such as experimental, comparative, or predictive correlational designs. The approach you should choose depends primarily on the goals of your research. Before deciding which of these quantitative research methods to choose, you should discuss your options with your mentor.

In this article:

• What is quantitative research design?
• A closer look at types of quantitative research
• Examples of quantitative research designs

What is quantitative research design?

In essence, dissertations seek to answer research questions. They can develop new theories, extend existing theories, or add to the body of knowledge in a particular area. Regardless of the purpose, research questions refer to the statement of the research problem, which is the heart of the dissertation.

For example, PhD students may seek answers to questions such as,Do teaching practices influence the motivation of special education students and to what extent?oDo office benefits affect worker productivity?

The findings you get from your research will help you get complete answers to your questions. However, in order to obtain these findings, you will need to develop a dissertation research design.

"Research design" refers to your approach to answering the underlying research questions. If you are writing a quantitatively based dissertation, your research design will focus on the collection and analysis of numerical data.

Before you can outline the details of your quantitative research design, you must decide whether your dissertation will be exploratory or inferential in nature. Exploratory research seeks to develop general ideas by investigating a topic in depth. On the contrary, final research aims to reach a final conclusion about the subject.

A closer look at types of quantitative research

Your quantitative research design is your strategy for conducting the research.doctoral research. In the process of determining your research design, you will need to answer questions such as the following:

• What are your overall goals and approach?
• What data collection methods will you use?
• What data collection procedures will you use?
• What are your criteria for selecting samples or selecting research subjects?
• How will you avoid the possibility of unintentional bias that could skew your results?
• How will you analyze your data?

You should also consider whether you will need primary or secondary data. "Primary data" refers to information you collect firsthand from sources such as research participants. "Secondary data" refers to information originally collected by other researchers; Most importantly, you will need to verify the reliability and validity of these sources.

Examples of quantitative research designs

As you think about the answers to the questions above, consider the main types of quantitative research designs:

• experimental research design
• Quasi-experimental research design
• comparative (causal)
• Correlational including predictive quantitative design
• general correlation

Descriptive quantitative design for your research

This type of quantitative research design is appropriate if you intend to measure variables and perhaps establish associations between variables. However, descriptive quantitative research design cannot establish causal relationships between variables.

Descriptive research is also known as "observational studies" because your role is purely that of an observer. The following are some of the types of descriptive studies you can do when writing your dissertation:

• Case study:This is an example of a fairly simple quantitative research design. It involves collecting data from a single research subject.
• Case series:If a researcher evaluates data from several research subjects, the study is called a "case series."
• Transversal study:In a cross-sectional study, researchers analyze variables in their sample of subjects. Then they establish non-causal relationships between them.
• Prospective study:Also called a "cohort study" or "longitudinal study," it involves the analysis of some variables at the beginning of the study. The researchers then further analyze the results at the end of the study. These studies can be conducted over a long period of time (eg researchers looking at people's eating habits and then determining the incidence of heart disease after 30 years).
• Case study and control:Investigators can compare cases or subjects with a particular attribute to cases lacking that attribute (controls). These are also called "retrospective studies".

Because the researcher's role is purely observational, they may not develop a hypothesis in advance, although some researchers may develop one before the research begins. Instead, a descriptive researcher develops a hypothesis after collecting data and analyzing it for their quantitative dissertation.

Design of correlational quantitative research

Because it also does not attempt to influence variables, correlational research is very similar to descriptive quantitative research design. Another similarity is that the researcher conducting the study measures or evaluates the variables involved. The main difference between descriptive and correlational studies is that correlational studies seek to understand the relationship between variables.

A correlational study can also determine whether this relationship is in a positive or negative direction. A positive correlation means that both variables move in the same direction. Conversely, a negative correlation means that the variables move in opposite directions.

For example, a positive correlation could be expressed as follows: "As a person lifts more weights, he develops more muscle mass." Meanwhile, a negative correlation could be expressed as follows: "As a waiter drops more trays, his tips decrease."

Note that correlational research can also produce results of zero correlation. For example, the presence of muscular waiters may not correlate with tips.

The fact that correlational research cannot be used to establish causation is a common point of confusion among new researchers. After all, it seems to be causal in nature that a server who frequently leaves trays receives less tips. The key point, however, is that correlational studies do not provide definitive proof that one variable leads to another variable.

Design of quantitative quasi-experimental research

In a quasi-experimental quantitative research design, the researcher attempts to establish a cause-and-effect relationship between one variable and another. For example, a researcher may find that high school students who study for one hour each day are more likely to score high on their tests. To develop this finding, the researcher would first measure the amount of time participants study each day (variable one) and then their test scores (variable two).

In this study, one of the variables is independent and the other is dependent. The value of the independent variable is not affected by other variables; the value of the dependent variable, however, depends entirely on changes in the independent variable. In the above example, length of study time is the independent variable and test scores are the dependent variable.

A quasi-experimental study is not a true experimental study because it does not randomly assign study participants to groups. Instead, it assigns them to groups specifically because they have a certain attribute or meet non-random criteria. Control groups are not strictly necessary, although researchers still often use them.

Design of experimental quantitative research

The design of experimental quantitative research uses a scientific approach. It establishes procedures that allow the researcher to test the hypothesis and systematically and scientifically study the causal relationships between variables.

All experimental quantitative research studies involve three basic steps:

1. The researcher measures the variables.
2. The researcher influences or intervenes with the variables in some way.
3. The researcher measures the variables again to determine how the intervention affected the variables.

An experimental quantitative study has the following characteristics:

• Nature and relationship of variables.
• A specific testable hypothesis
• Subjects assigned to groups based on predetermined criteria
• Experimental treatments that change the independent variable
• Measurements of the dependent variable before and after the change of the independent variable

A scientific experiment may use a completely randomized design in which each study participant is randomly assigned to a group. Alternatively, you can use a randomized block design in which research participants who share a particular attribute are grouped together. In each case, participants receive random treatments within their groups.

Design of comparative (causal) research

Comparative causal research, or ex post facto research, studies the reasons behind a change that has already occurred. For example, researchers may use a cause-and-effect comparative design to determine how a new diet affects children who have already started it. This type of research is especially common in sociological and medical circles.

There are three types of comparative causal research, including:

• Investigating the effects of group participation
• Investigating the causes of group participation
• Investigation of the consequences of the change in the group

Although comparative causal research designs can provide information about relationships between variables, researchers cannot use them to define why an event occurred. This is because the event has already happened, so researchers cannot be sure what caused it and what the effects were.

Comparative causal studies involve the same general steps:

• Recognize phenomena and think about the causes or consequences of these phenomena.
• Make a specific problem statement
• Create one or more hypotheses.
• Select a study group
• Compare the group on one or more variables to control for variables and eliminate within-group differences (this step may vary depending on the type of causal comparative study being conducted)
• Select the instruments to be used in the study.
• Compare groups using one or more different variables

Causal comparative studies are similar to correlational studies, but while both investigate relationships between variables, causal comparative studies compare two or more groups, and correlational studies evaluate each variable on a single group. Although correlational studies involve multiple quantitative variables, causal comparative studies involve one or more categorical variables.

Prospective PhD students at Grand Canyon University (GCU) can choose from a wide variety of programs in a variety of fields fromFaculty of Doctoral Studies. That includesDoctor of Philosophy in General Psychology: Psychology of Performance (Quantitative Research)class iDoctor of Science in Organizational Leadership (quantitative research)degree. Fill out the form on this page to explore your PhD options at GCU.

Approved by the Vice-Dean of the Faculty of Doctoral Studies on April 21, 2023.