Research Design & Statistics

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analysis of covariance (ancova)

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an extension of the anova used to increase the efficiency of the analysis by statistically removing variability in the dv that is due to an extraneous variable. when using the ancova, each person's score on the dv is adjusted on the basis of his/her score on the extraneous variable.

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between groups designs

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studies in which the effects of the different levels of one or more iv's are compared by administering each level or combination of levels to a different group of subjects

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cohort (intergenerational) effects

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the effects of being part of a group (cohort) that was born at a particular time and, as a result, was exposed to unique educational, cultural, and other experiences. cohort effects can confound the results of a cross-sectional study since any observed differences between age groups might be due to these effects rather than to differences in age only.

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cross-sequential studies

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studies conducted to assess the effects of aging and/or developmental changes over time. cross-sequential studies help overcome the shortcomings of cross-sectional and longitudinal research by combining both methodologies.

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discriminant function analysis

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the multivariate technique used when there are two or more predictors and one criterion that is measured on a nominal scale (i.e., that is measured in terms of unordered groups or categories).

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experimenter expectancy

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the bias that an experimenter can introduce into a research study as a result of his/her expectations about the study's outcomes. when an experimenter's expectations directly affect research participants, they act as a source of demand characteristics.

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factorial anova

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the type of anova used when a study includes two or more iv's (i.e., when the study has used a factorial design). also referred to as a two-way anova, three-way anova, etc., with the words "two" and "three" referring to the number of iv's.

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heteroscedasticity

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refers to unequal variances in two or more samples or populations.

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interaction

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an effect that occurs when the impact of different levels of one independent variable differ at different levels of another variable. when a study has a significant interaction, the main effects should be interpreted with caution.

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leptokurtic

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a distribution that is more "peaked" than the normal distribution, i.e., a distribution in which scores are "piled up" in the central region of the distribution with a relatively few scores in the tails.

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manipulated variable

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an independent variable that is controlled by the experimenter. when the experiementer can identify the levels of the variable and determine who will receive which levels, the variable is a manipulated variable.

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mixed design

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a research design in which both between groups and within subjects comparisons can be made.

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multiple regression equation

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the statistical technique used for predicting a score on a criterion based on performance on two or more predictors. use of a multiple regression equation requires that the criterion be measured on either an interval or ratio scale. ideally, predictors included in a multiple regression equation will have low correlations with each other and high correlations with the criterion.

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nominal scale

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a scale of measurement in which the variable is divided into unordered groups or categories. when a variable is measured on a nominal scale (or is treated as though it were measured on a nominal scale), the data to be described or analyzed are frequency data; i.e., the frequency of observations in each group or category.

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one-tailed test

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a statistical test that places the entire rejection region in only one tail of the sampling distribution. used when the alternative hypothesis is directional.