Psychology
Experimental Designs
Experimental designs in psychology refer to the structured plans for conducting research to investigate cause-and-effect relationships. They involve manipulating independent variables to observe their effects on dependent variables. Common types of experimental designs include pre-test/post-test control group design, factorial design, and within-subjects design. These designs are essential for drawing valid conclusions about the impact of variables on behavior and mental processes.
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10 Key excerpts on "Experimental Designs"
eBook - PDF- Phyllis Tharenou, Ross Donohue, Brian Cooper(Authors)
- 2007(Publication Date)
- Cambridge University Press(Publisher)
Experimental and quasi-Experimental Designs 35 an experimental condition or group derived by a manipulation or inter-vention to force it to occur (e.g., introducing a stimulus); this is the independent variable ; a control group (or several groups) called controls that do not get the experimental treatment; a controlled environment where no other event can influence what is happening. The experimental manipulation is therefore the only thing that changes; random allocation of participants to experimental and control groups so that an individual could just as likely end up in the experimental group as the control group; and the dependent variable is measured after the introduction of the treatment, in both the experimental/treatment group and the con-trol group, to see if there was a change in the experimental group but not in the control group. The central features of a true experimental design therefore are manipulation and control (Sekaran, 1992 ). An essential element of true experiments is randomisation of cases to experimental and control groups. A thoughtfully designed experiment provides the required controls that enable the researcher to reject alternative explanations, thereby allowing him or her to draw strong causal inferences (Raulin & Graziano, 1995 ). True experiments are strong on internal validity; that is, the ability to make causal inferences. They do so by control-ling all the variables, other than the cause, then manipulating the cause to introduce it as a treatment, and then comparing the effect on the dependent variable (the effect). Creswell ( 2003 ) has provided a useful checklist of questions for designing an experimental proce-dure. This checklist is presented in the appendix at the end of this chapter. Quasi-Experimental Designs Quasi-Experimental Designs also provide the researcher with the opportunity to assess the effects of interventions or manipulations. However, it is important to keep in mind that they are not true experiments.
- Aparna Raghvan(Author)
- 2020(Publication Date)
- Society Publishing(Publisher)
To put it in short, a research methodology is, “a way to systematically solve a research problem.” The environments, at some points of time, may get quite complicated. Hence, it becomes very important to understand the processes taking place in these environments, and study them in real-time and conditions. In Experimental and Quasi-Experimental Research 55 such cases, quasi-experiments play a vital role, as they tend to provide the researchers with an understanding of the intricate nature of the processes and the appearance of the phenomena around the world, by making them able to focus on the environments in the natural settings and the real-time. However, even with such a great property of providing the researchers with a real-time setting to study the processes, the quasi-experiments tend to demonstrate some weaknesses and disadvantages. An experiment may be considered as a study that enables the researcher to work on some of the independent variables and consequently report the results of the process. They serve as a significant way of taking a look on the relationship between the causes of a phenomenon and the effects it may have. There is a popular belief in the research community that the experiments must be taken to be the ‘gold standard’ which should determine the manner in which other researches must be designed or judged. The conduct of the experiments may take place in both the places—the laboratory and in the times related to real life. 3.2. KINDS OF Experimental Designs The research designs may be considered to be of two fundamental kinds: • True experiments; and • Quasi-experiments. Both these kinds of Experimental Designs aimed at finding the reason for the happening of the various phenomena. Generally, the preferred design of experiments is true experiment as these are the ones that have the characteristic of controlling all the factors which may have significance in a particular phenomenon and may be of interest in that phenomenon.
eBook - PDF- Donald Ary, Lucy Jacobs, Christine Sorensen Irvine, David Walker(Authors)
- 2018(Publication Date)
- Cengage Learning EMEA(Publisher)
260 PART TWO QUANTITATIVE RESEARCH 10-6 Other Randomized Experimental Designs The Experimental Designs we have discussed so far use at least two groups of subjects, one of which is exposed to the treatment (independent variable) and the other that does not receive the treatment or is exposed to another level of the treatment. The researcher then compares the dependent variable scores for the different treatment groups. The essential feature of these designs is that they compare separate groups of subjects in order to determine the effect of the treat-ment. When the independent variable is manipulated in this way, we have what is called a between-subjects design . For example, a researcher who compares read-ing achievement scores for students taught by one method with scores for an equivalent group of students taught by a different method is using a between-subjects design. However, the manipulation of an independent variable does not have to involve different groups of subjects. It is possible to use Experimental Designs in which the same participants are exposed to different levels of the independent variable at differ-ent times. For example, a researcher might measure the learning of nonsense syllables by one group of students under different levels of anxiety or the math performance scores of a group of students when music is played in the classroom versus no music. This type of design in which a researcher observes each individual in all of the differ-ent treatments is called a within-subjects design . It is also called a repeated-measures design because the research repeats measurements of the same individuals under dif-ferent treatment conditions. The main advantage of a within-subjects design is that it eliminates the problem of differences in the groups that can confound the findings in between-subjects research.
eBook - PDFResearch Methods For Business
A Skill Building Approach
- Roger Bougie, Uma Sekaran(Authors)
- 2021(Publication Date)
- Wiley(Publisher)
CHAPTER 11 164 Experimental Designs In Chapter 7, we examined basic research strategies. We distinguished experimental from non- experimental approaches and explained that Experimental Designs are typically used in deductive research where the researcher is interested in establishing cause-and-effect relationships. In the last three chapters, we discussed non-experimental approaches to primary data collection. In this chapter, we look at Experimental Designs. Consider the following three scenarios. INTRODUCTION Example Cause-and- effect rela- tionship after randomization Scenario A A manufacturer of luxury cars has decided to launch a global brand commu- nications campaign to reinforce the image of its cars. An 18-month campaign is scheduled that will be rolled out worldwide, with advertising in television, print and electronic media. Under the title ‘Bravura’, a renowned advertising agency developed three different campaign concepts. To determine which of these concepts is most effective, the car manufacturer wants to test their effects on the brand’s image. But how can the car manufacturer test the effectiveness of these concepts? Scenario B A study of absenteeism and the steps taken to curb it indicates that com- panies use the following incentives to reduce it: 14% give bonus days; 39% offer cash; 39% present recognition awards; 4% award prizes; 4% pursue other strategies. LEARNING OBJECTIVES After completing Chapter 11, you should be able to: 1. Describe lab experiments and dis- cuss the internal and external validity of this type of experiment. 2. Describe field experiments and dis- cuss the internal and external validity of this type of experiment. 3. Describe, discuss and identify threats to internal and external validity and make a trade-off between internal and external validity. 4. Describe the different types of experi- mental designs. 5. Discuss when and why simulation might be a good alternative to lab and field experiments.
No longer available |Learn more- Charles Stangor, , , (Authors)
- 2014(Publication Date)
- Cengage Learning EMEA(Publisher)
All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. 278 Chapter 14 QUASI-EXPERIMENTAL RESEARCH DESIGNS We have seen in Chapter 10 that the strength of experimental research lies in the ability to maximize internal validity. However, a basic limitation of experi-mental research is that, for practical or ethical reasons, the independent vari-ables of interest cannot always be experimentally manipulated. In this chapter, we will consider research designs that are frequently used by researchers who want to make comparisons among different groups of individuals but can-not randomly assign the individuals to the groups. These comparisons can be either between participants (for instance, a comparison of the scholastic achievement of autistic versus nonautistic children) or repeated measures (for instance, a comparison of the mental health of individuals before and after they have participated in a program of psychotherapy). These research de-signs are an essential avenue of investigation in domains such as education, human development, social work, and clinical psychology because they are frequently the only possible approach to studying the variables of interest. Program Evaluation Research As we have seen in Chapter 1, one type of applied research that involves the use of existing groups is program evaluation research (Campbell, 1969; Rossi & Freeman, 1993).
- Paul M. Kellstedt, Guy D. Whitten(Authors)
- 2018(Publication Date)
- Cambridge University Press(Publisher)
4.2 Experimental Research Designs 91 YOUR TURN: Thinking creatively to increase the external validity of the stimulus In the example above about how lab experiments sometimes force exposure (of media content, for example) on to participants, can you think of any creative way that an experimenter might be able to circumvent this problem? Try to imagine how we could do the experiment differently. Now go see how it was done. Read Arceneaux, Johnson, and Murphy (2012) here: http://www.jstor.org/stable/10.1017/s002238161100123x What difference did it make on the results about media effects on public opinion? Experimental research designs, at times, can be plagued with a third disadvantage, namely that they carry special ethical dilemmas for the researcher. Ethical issues about the treatment of human participants occur frequently with medical experiments, of course. If we wished to study experimentally the effects of different types of cancer treatments on survival rates, this would require obtaining a sample of patients with cancer and then randomly assigning the patients to differing treatment regimens. This is typically not considered acceptable medical practice. In such high-stakes medical situations, most individuals value making these decisions themselves, in consultation with their doctor, and would not relinquish the important decisions about their treatment to a random- number generator. Ethical situations arise less frequently, and typically less dramatically, in social science experimentation, but they do arise on occasion. During the behavioral revolution in psychology in the 1960s, several famous exper- iments conducted at universities produced vigorous ethical debates. Psy- chologist Stanley Milgram (1974) conducted experiments on how easily he could make individuals obey an authority figure.
eBook - PDF- James B. Schreiber, Kimberly Asner-Self(Authors)
- 2011(Publication Date)
- Wiley(Publisher)
C H A P T E R 7 Experimental and Nonexperimental Research Design KEY IDEA Protecting your fort from attack: A well-thought-out quantitative design. 150 POINTS TO KNOW Distinguish between independent, dependent, mediator, and moderator variables. Explain the limitations of experimental and nonexperimental research designs. Describe the three components of causality. Describe the types of experimental and nonExperimental Designs with related basic research questions. Determine the defining attributes of single-subject, longitudinal, preexperimental, quasi-experimental, and true Experimental Designs. Identify the main components of advanced techniques. Description Analysis Interpretation Sample Design Data Collection Research Questions Literature Review Literature Review Literature Review Literature Review 152 Chapter 7 • Experimental and Nonexperimental Research Design DESIGN FOR STRENGTH AND ELEGANCE We think of research design as building a strong structure that is resistant to attack. By attack, we mean critics who will look for ways not to believe your observations; the critics of your research will look for weaknesses. Elegance is a bit more difficult to design because it interacts with the instruments or stimuli created for participants. Jim is continually struck by the elegance of the developmental experiments of the 1960s, such as the ‘‘visual cliff’’ study by Gibson and Walk (1960). It is a solid design with a great stimulus. For this chapter, you should begin to see which of the types of designs examined might align with the research questions or hypotheses you have. To aid in your understanding, we created a chart with basic research designs and the types of analyses that align to different types of designs. This appears in Table 7.15 after the discussion of the Experimental Designs. Before we look at experimental research design, let’s review some material that will help along the way.
eBook - PDF- Dana S. Dunn(Author)
- 2012(Publication Date)
- Wiley(Publisher)
Other approaches to performing randomization can be found in Snedecor and Cochran (1980). As ideas, chance and randomization actually have a very interesting place in the history of ideas. For further exploration of their relevant history, consult Hacking (1975) or Gigerenzer et al. (1989). 92 Basic Experimental Design have different experiences, and whether the nature of those experiences leads to measurable, behavioral differences is determined by examining the dependent variable. Simple two-cell designs have both advantages and disadvantages. A clear strength is that such designs, with one independent variable, are relatively straightforward to conduct. A second, related strength is that learning whether the independent variable created a change in the dependent variable is usually easy to determine. These designs are helpful when little is known about a research question. Thus, social psychologists often use two-cell designs when they are trying to establish whether a hypothesized effect, as indicated by a between-group difference, is really there. These strengths, however, can also pose disadvantages in that studies with one independent variable can be limiting where broader information about a topic is concerned. Their “present- versus-absent” quality (e.g., good mood vs. neutral mood) does not tell us about the subtleties or complexities of human behavior (e.g., can some positive moods be stronger than others and, if so, with what effect on problem solving?). One way to think about studies with one independent variable is that they create more questions than they answer. The quality of these questions often requires that a researcher manipulate two, three, or even more independent variables within one study in order to address richer behavioral questions.
eBook - PDFEducational Research
A Contextual Approach
- Ken Springer(Author)
- 2015(Publication Date)
- Wiley(Publisher)
Each type can be understood and evaluated in terms of how well it handles threats to internal and external validity. True Experimental Designs True Experimental Designs are based on random assignment of participants to an experimental group and at least one control and/or comparison group. In this section I will describe some of the most prominent examples of true Experimental Designs. Types of Experimental Design 195 RANDOMIZED PRETEST–POSTTEST CONTROL GROUP DESIGN The random- ized pretest–posttest control group design, described at length at the outset of the chapter and summarized in Table 7.2, begins with random assignment of partici- pants to experimental and control (or comparison) groups, followed by pretesting of each group, administration of each condition, and then posttesting of the groups. The extent of control inherent in this design is greater than in others, because in the ideal case, the only difference in the experiences of the two groups would be the experimental manipulation. The use of a pretest helps identify differential selection effects (although one potential risk of this design is the possibility of pretest–treatment interaction). Random assignment helps prevent differential selec- tion effects from occurring in the first place. Moreover, certain kinds of subject effects and selection–treatment interactions are less likely when random assignment is used. RANDOMIZED POSTTEST-ONLY CONTROL GROUP DESIGN The randomized posttest-only control group design is simply a randomized pretest–posttest control group design without the pretest. When using this design, researchers assume that randomization will prevent any differences between the groups that would result in selection effects. One strength of this design is that it excludes the possibility of pretest–treatment interactions, since the dependent variable is measured only once.
eBook - PDFExperimental Design and Statistics for Psychology
A First Course
- Fabio Sani, John Todman(Authors)
- 2008(Publication Date)
- Wiley-Blackwell(Publisher)
We would have arranged things so that 20 participants saw a funny video and then attempted to solve some logical problems, and on another occasion saw a neutral video and attempted to solve the same number of logical problems. In this way, participants may be said to ‘act as their own control’. An experimental design using the same participants in the two conditions of the experiment is described as a repeated measures design. Note that one advantage of using this design is that we may need only half the number of participants (20 instead of 40 in our example) to give us the same number (20) of scores in each condition as there were in the independent groups design. Despite being effective for controlling participant variables, a repeated measures design may cause problems. Consider our experiment. Suppose the participants watch the neutral video (control condition) first and attempt some problems. Then, when they come to watch the funny video and attempt some more problems, they could capitalize on the practice and experience gained when they took the same type of test in the control condition. Therefore, if in the experimental condition we obtained a better performance than in the control condition we would not know whether this was due to the fact that in the experimental condition participants had a positive mood, or to the fact that they had more familiarity with the test. This problem is known as an order effect , which means that scores on the DV in each condition may depend on which condition comes first and which comes second. It is, of course, a particular type of confound. THE NATURE OF PSYCHOLOGY EXPERIMENTS (II): VALIDITY 28 The best way to deal with order effects is to use counterbalancing . This involves giving the two conditions of the experiment in different orders to two randomly selected halves of the participants.
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