7 How to Decide Which Variables to Manipulate and Measure Marziyeh Rezaee.

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Presentation transcript:

7 How to Decide Which Variables to Manipulate and Measure Marziyeh Rezaee

Choosing an Independent Variable the most important decision Operational definitions of the independent and dependent variables disagree Psychology researchers operational definitions require complex operational definitions literature search

CHOOSING THE RANGE OF YOUR INDEPENDENT VARIABLE Range: the difference between the highest and lowest level of the variable How do we determine what the range should be? 1. Be Realistic 2. Select a Range That Shows Effect :a range that is large enough to show an effect of the independent variable on the dependent variable 3. Do a Pilot Experiment :(small-scale version of the experiment) if your experiment is original and nobody else has used an independent variable similar to yours, you may choose to do a pilot experiment.

Choosing a Dependent Variable OPERATIONAL DEFINITIONS With dependent variables, not only do we have to focus on determining an operational definition, but we also have to know whether the measurement is reliable and valid.

RELIABILITY A measuring instrument is perfectly reliable if we get exactly the same result when we repeat the measurement a number of times under comparable conditions. The reliability of a standardized test will already have been tested, and a statistical value indicating this reliability can be found in the test manual.

determine its reliability yourself test–retest reliability, in which the same test is simply repeated on the same group at a later time. (:alculating a correlation coefficient using two scores from each test taker) alternative-form method method. A second test having items similar to the first is constructed and given to the same people. the split-half technique in which a single test is statistically split into halves (such as using odd versus even questions) and scores for the two halves are correlated.

Validity refers to confirming whether we are measuring what we want to measure. face validity content validity predictive validity Concurrent validity

Single Dependent Variables Multiple Dependent Variables Composite Dependent Variables

Physiological Measures Probably the most popular types of indirect variables are physiological measures, which are based on the idea that if the behavior is a private event, such as an emotion, perhaps the physiology of the body will change along with the private event.

Physiological Measures

Behavioral Measures Indirect behavioral measures are particularly important in some areas of cognitive psychology.

Dual-task methodology offers an indirect way of determining the processing requirements of a task while it is being performed.

8 How to Decide on a Between-Subjects versus Within-Subject Design

between-subjects design expose each individual to only one level of the independent variable

within-subject design expose each individual to all levels

■ Between-Subjects Experiments ADVANTAGES:ADVANTAGES: exposure to one of the levels of the independent variable cannot contaminate the participant’s behavior under other levels. DISADVANTAGESDISADVANTAGES It is that the groups assigned to each level of the independent variable might not be equivalent to each other on some dimension, and this dimension might bias the behavior being measured. ***But if participant are randomly assigned to groups, it is not probable that this would happen. *Random assignment of participants for between-subjects experiments is actually quite effective in removing potential bias among groups.

Within-Subject Experiments PRACTICAL ADVANTAGES Fewer participants are required.// Fewer time STATISTICAL ADVANTAGES compare the differences between the average performances at the two levels with an stimate of how variable the performance within each of the levels is.

Within-Subject Experiments DISADVANTAGES carry-over effects: the way previous exposures have affected participants  occurs when participating in a prior condition influences participation in a current condition order effects: the behavior resulting from a level of the independent variable depends upon the order in which that level was presented.  occurs when the absolute order of conditions influences the results; later performance is often better than early performance because of practice ***. Learning is one of the most common order effects.

COUNTERBALANCING One way to minimize an order effect like learning is to counterbalance.  determine the order of presentation of the conditions in a repeated measures design; they attempt to control (not eliminate) order effects. You also admit that you cannot control it or randomize it out of existence. so you attempt to distribute an equal amount of the confounding effect to each level of your independent variable. Counterbalancing removes confounding variables from an experiment by giving slightly different treatments to different participant groups.

One of the more frequently used counterbalancing schemes is called ABBA counterbalancing.

ABAB COUNTERBALANSING

What is a Counterbalanced Measures Design? The simplest type of counterbalanced measures design is used when there are two possible conditions, A and B. As with the standard repeated measures design, the researchers want to test every subject for both conditions. They divide the subjects into two groups and one group is treated with condition A, followed by condition B, and the other is tested with condition B followed by condition A.

counterbalancing schemes are based on certain assumptions. One assumption of ABBA counterbalancing is that the confounding effect is linear—that it forms a straight line.  The ABBA counterbalancing can eliminate the effects of a confounding variable in within-subject experiments, but only if the confounding effect is linear. If the effect is nonlinear, we must choose a different counterbalancing technique or else design a between- subjects experiment

This assumption is: symmetrical transfer: you are still making the assumption that the effect of having B follow A is just the reverse of the effect of having A follow B.

complete counterbalancing : occurs when all possible orderings of the condition are used in the experiment; randomly assign participants to the various orders. partial counterbalancing : is a system of counterbalancing that ensures that each treatment condition occurs first for one group of participants, second for one group, third for one group, and so on, but does not require that every possible order of treatment conditions be used.

Latin Square A partial counterbalancing scheme often used with independent variables having more than two levels is a Latin Square, which ensures that each level appears at every position in the order equally often.