2.3.2: Quantitative Designs

Quantitative Methods

Quantitative methods use research methods that rely on collecting and analyzing data using statistical techniques to understand phenomena, measure relationships between variables, and/or test hypotheses.

Surveys

Surveys are familiar to most people because they are so widely used. Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online. A survey involves asking a standard set of questions to a group of subjects. In a highly structured survey, subjects are forced to choose from a response set such as “strongly disagree, disagree, undecided, agree, strongly agree”; or “0, 1-5, 6-10, etc.” This is known as the Likert Scale. Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time. Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.

Of course, surveys can be designed in various ways. They may include forced-choice questions and semi-structured questions, in which the researcher allows the respondent to describe or provide details about specific events. One of the most challenging aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather than choosing “undecided” each time. Knowing that 30% of respondents are undecided is of little use! A lot of time and effort should be spent on constructing survey items. One of the benefits of having forced-choice items is that each response is coded, allowing results to be quickly entered and analyzed using statistical software. Analysis takes much longer when respondents provide lengthy responses that need to be analyzed in a different way. Surveys help examine stated values, attitudes, opinions, and reporting on practices. However, they are based on self-report or what people say they do rather than on observation, and this can limit accuracy.

Developmental Designs

Developmental designs are techniques used in developmental research, as well as in other areas. These techniques try to examine how age, cohort, gender, and social class impact development.

Longitudinal Research

Longitudinal research involves beginning with a group of people who may be of the same age and background and measuring them repeatedly over a long period of time. One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.

Figure \(\PageIndex{1}\): A longitudinal research design. Image by NOBA is licensed under CC BY-NC-SA 4.0.

A problem with this type of research is that it is very expensive, and subjects may drop out over time. The Perry Preschool Project, which began in 1962, is an example of a longitudinal study that continues to provide data on children’s development.

Cross-sectional Research

Cross-sectional research involves beginning with a sample that represents a cross-section of the population. Respondents who vary in age, gender, ethnicity, and social class may be asked to complete a survey about their television program preferences or attitudes toward using the Internet. The attitudes of males and females could then be compared, as could attitudes based on age. In cross-sectional research, respondents are measured only once.

Figure \(\PageIndex{2}\): A cross-sectional research design. Image by NOBA is licensed under CC BY-NC-SA 4.0.

This method is much less expensive than longitudinal research, but does not allow the researcher to distinguish between the impact of age and the cohort effect. Different attitudes about the use of technology, for example, might not be altered by a person’s biological age as much as their life experiences as members of a cohort.

Sequential Research

Sequential research involves combining aspects of the previous two techniques, beginning with a cross-sectional sample and measuring it through time.

Figure \(\PageIndex{3}\): A sequential research design. Image by NOBA is licensed under CC BY-NC-SA 4.0.

This is the perfect model for looking at age, gender, social class, and ethnicity. But the drawbacks of high costs and attrition are here as well.¹⁶

Table \(\PageIndex{1}\): Advantages and Disadvantages of Different Research Designs.

Type of Research Design	Advantages	Disadvantages
Longitudinal	Examines changes within individuals over time Provides a developmental analysis	Expensive Takes a long time Participant attrition Possibility of practice effects Cannot examine cohort effects
Cross-sectional	Examines changes between participants of different ages at the same point in time Provides information on age-related change	Cannot examine change over time Cannot examine cohort effects
Sequential	Examines changes within individuals over time Examines changes between participants of different ages at the same point in time Can be used to examine cohort effects	May be expensive Possibility of practice effects

Research Methods in Developmental Psychology by Angela Lukowski and Helen Milojevich is licensed under a CC BY-NC-SA 4.0.

Experiments

Experiments are designed to test hypotheses (or specific statements about the relationship between variables) in a controlled setting, aiming to explain how certain factors or events produce specific outcomes. A variable is anything that changes in value. Concepts are operationalized or transformed into variables in research, which means that the researcher must specify exactly what will be measured in the study.

Three conditions must be met to establish cause and effect. Experimental designs help meet these conditions. 1. The independent and dependent variables must be related to each other. In other words, when one is altered, the other changes in response. (The independent variable is something altered or introduced by the researcher. The dependent variable is the outcome or the factor affected by the introduction of the independent variable. For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise, and the dependent variable would be stress. 2. The cause must come before the effect. Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable, thereby establishing a baseline. So we would measure the subjects’ level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels. (Observational and survey research do not always allow us to look at the timing of these events, which makes understanding causality problematic with these designs.) 3. The cause must be isolated. The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see. The experimental design helps make this possible. In an experiment, we would ensure that our subjects’ diets remained constant throughout the exercise program. Otherwise, the diet might actually be causing a change in stress levels rather than exercise.

A basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the experimental group or the control group. The experimental group is the group that will be exposed to an independent variable or condition that the researcher is introducing as a potential cause of an event. The control group will be used for comparison and will have the same experience as the experimental group, but will not be exposed to the independent variable. After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred. If so, we are in a better position to suggest that the independent variable caused the change in the dependent variable.

The major advantage of the experimental design is that it helps to establish cause-and-effect relationships. A disadvantage of this design is the difficulty of translating much of what happens in a laboratory setting into real life.

References, Contributors, and Attributions

16. Research Methods by Lumen Learning is licensed under CC BY 4.0

18. Confidentiality and Informed Consent: Issues for Consideration in the Preservation of and Provision of Access to Qualitative Data Archives by Louise Corti, Annette Day & Gill BackhouseSource is licensed under CC BY 4.0 (modified by Jennifer Paris); "No thank you, not today": Supporting Ethical and Professional Relationships in Large Qualitative Studies by Lisa J. Blodgett, Wanda Boyer & Emily TurkSource is licensed under CC BY 4.0 (modified by Jennifer Paris)

19. Research Methods in Developmental Psychology by Angela Lukowski and Helen Milojevich is licensed under a CC BY-NC-SA 4.0