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Questions:. Will the test be curved if the scores are very low? Which type of probability sampling mathod is most commonly used? Is the validity of a research study related to the validity of the measures in the research study?

Mercy
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Questions:

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  1. Questions: • Will the test be curved if the scores are very low? • Which type of probability sampling mathod is most commonly used? • Is the validity of a research study related to the validity of the measures in the research study? • If there are some threats to your study and you are unable to completely control them can your results still be taken as valid? • Would your research study become weak if your predictions of confounding variables were off? Or could that fall under error? • If extraneous and confounding variables exist, how do you account for them in the experiment to keep from affecting the results?

  2. More questions: • Why is the research strategy the 5th step in the process? It seems like it should be one of the first things one should choose! • For our research project, I am confused about Step 8, evaluating the data, and step 9, reporting the results. What exactly do you want us to include in these steps? Is this related to what type of research strategy we use? • When you say to include a reference at the end of our presentation do you mean the different studies we looked at? Do you want us to cite the source(s) in APA style or just put the name of the source?

  3. Experimental Research Strategy Chapter 7 Dusana Rybarova Psyc 290B May 23 2006

  4. Outline: • Cause-and-effect relationships • Elements of an experiment • Dealing with extraneous variables • Control groups • Manipulation checks • Increasing external validity: Simulation and Field studies

  5. 1. Cause-and-effect relationships • the term experiment is often used as a generic label for any kind of scientific research • however, a research study must meet specific criteria to qualify as an experiment • the goal of experimental strategy is to establish the existence of a cause-effect relationship between two variables • in an experiment we are trying to show that changes in one variable are directly responsible for causing changes in the other variable

  6. Causation and the third-variable problem • the variables that we want to manipulate and study rarely exist in isolation • in a real world we are usually exposed to a tangled network of interrelated variables • it is essential that a researcher separates and insolates the specific variables being studied • it is possible that a third (unidentified) variable is controlling the two variables and is responsible for producing the observed relation • e.g. • Is the fitness program causing higher productivity or • some other variable such as being more fit or healthier is influencing both the tendency to participate in a fitness program and to have higher productivity?

  7. Causation and the directionality problem • although a research study may establish a relationship between two variables, the problem is determining which variable is the cause and which is the effect • e.g. Is watching violent movies causing children to be aggressive or is it that aggressive children like to watch violent movies? • another example is the relationship between assertiveness and success

  8. Cause and effect relation and external validity • to establish a cause-and-effect relation, an experiment must control nature, essentially creating an “unnatural” situation wherein the two variables being examined are isolated from the influence of other variable and wherein the exact character of a relationship can be seen clearly • just because an experiment takes place in an unnatural environment (i.e. lab) does not necessarily imply that the results are unnatural • the goal of any experiment is to reveal the natural underlying mechanisms and relationships that may be otherwise obscured

  9. 2. Elements of an experiment • in order to show that there is a cause-effect relationship between two variables we have two goals: • it must be shown that changes in one variable cause changes in he other variable • an experiment must rule out the possibility that the changes are caused by some other variable • these two goals lead to two characteristics differentiating experiments and other research strategies • manipulation of one variable while measuring a second variable • control of other, extraneous variables

  10. Manipulation and measurement • the primary purpose of manipulation is to allow researchers to determine the direction of a relationship • e.g. change in the position of the switch vs. change in brightness of the light or depression and insomnia • a second purpose of manipulation is to give the researcher command of one of the variables being studied • experimenter is the one determining the manipulation • independent variable • is the variable manipulated by the researcher • the independent variable usually consists of two or more treatment conditions to which participants are exposed (e.g. changes in room temperature) • dependent variable • is the variable that is observed for changes in order to assess the effects of manipulating the independent variable • the dependent variable is typically a behavior or a response measured in each treatment condition (e.g. test performance)

  11. Manipulation and measurement(cont.) • extraneous variable • all variables in the study other than the independent and dependent variables • treatment condition • a situation or environment characterized by one specific value of the manipulated variable • an experiment contains two or more treatment conditions that differ according to the values of the manipulated variable • levels • the different values of the independent variable selected to create and define the treatment conditions are called the levels of the independent variable

  12. Control and extraneous variables • the purpose of an experiment is to show that the manipulated variable is responsible for the changes observed in the dependent variable • therefore, an experiment must rule out any other possible explanation for the observed changes – that is, eliminate all confounding variables • e.g. Pavio’s research on imagery causing better memory with the possible confounding variable of meaningfulness (or abstractness)

  13. 3. Dealing with extraneous variables • an experimental researcher must prevent any extraneous variable from becoming a confounding variable • this is the basic purpose of control within an experiment • confounding variable has two important characteristics • extraneous variable becomes a confounding variable only if it influences the dependent variable • a confounding variable must vary systematically with the independent variable (e.g. IQ and memory) • There are two standard methods for controlling extraneous variables: • control by holding constant or matching • control by randomization

  14. Control by holding constant or matching • the impact of an extraneous variable on the results can be eliminated by holding it constant • e.g. all individuals in the experiment will be observed in the same room, at the same time of day, by the same researchers, the individuals have the same IQ etc. • the impact of an extraneous variable on the results can be minimized by matching the levels of the variable across treatment conditions • e.g. 10 males and 20 females can be assigned to each separate treatment condition • in this way we eliminate possible variation across treatments

  15. Control by randomization • randomization is the use of a random process to help avoid a systematic relationship between two variables • the intent of randomization is to disrupt any systematic relation between extraneous variables and the independent variable and thereby prevent the extraneous variable from becoming a confounding variable • e.g. IQ and memory or time of the day • random assignment is the use of a random process to assign participants to treatment conditions • randomization is a powerful tool for controlling extraneous variables; its primary advantage is that it offers a method for controlling a multitude of variables simultaneously and does not require specific attention to each extraneous variable

  16. 4. Control groups • sometimes a researcher wishes to evaluate only one treatment rather than compare a set of different treatments; in such case he selects an experimental group and a control group • the term experimental group refers to the treatment condition in an experiment • the term control group refers to the no-treatment condition in an experiment • there are two types of control groups: • no-treatment control groups • placebo control groups

  17. no-treatment control group • is a condition in which the participants do not receive the treatment being evaluated • this group provides the standard of normal behavior or baseline against the treatment condition • e.g. anxiety treatment group vs. no treatment control group • placebo control groups • placebo is a term for a fake medical treatment such as a sugar pill or water injection • placebo effect refers to a response by a participant to an inert medication that has no real effect on the body; the placebo effect occurs simply because the individual thinks the medication is effective • e.g. use of inactive drugs or non-specific psychotherapy (therapy with the therapeutic components removed)

  18. 5. Manipulation checks • The purpose of the manipulation check is to assess whether the independent variable had the intended effect on the participant • Two ways to check manipulation • An explicit measure of the independent variable • E.g. a measure of mood in an mood inducing experiment • Questionnaire for participants after the experiment whether they perceived and how they interpreted the manipulation • E.g. masked priming • Manipulation checks are especially important in • Participant manipulations • E.g. frustration task • Simulations • Real world situations in the lab • Placebo controls • Whether participants believed that they received a real drug

  19. 6. Increasing external validity: simulation and field studies • when research seeks cause-and-effect explanations for behavior in real-world situations, it is essential that the experimental results generalize outside the confines of the experiment • two standard techniques to accomplish this: • simulation • field studies

  20. simulation • is the creation of conditions within an experiment that simulate or closely duplicate the natural environment in which the behaviors being examined would normally occur • e.g. the Stanford prison study or prisoner’s dilemma studies • field studies • a field study is an experiment conducted in a place that the participant or subject perceives as a natural environment • e.g. a variety of staged emergencies such as a flat tire, a lost wallet, a collapsed victim

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