Introduction to “Kinds” of 2-way Factorial Designs Incorporating within-groups comparisons ANOVA for BG, MG & WG designs Applying LSD mmd to kxk designs.

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Introduction to “Kinds” of 2-way Factorial Designs Incorporating within-groups comparisons ANOVA for BG, MG & WG designs Applying LSD mmd to kxk designs

When working with factorial designs we will consider two major types of IVs… those that are investigated using a between groups comparison different participants in the conditions of the IV (BG) those that are investigated using a within-groups comparison the same participants are in all conditions of the IV (WG) Thus, there are three “kinds” of 2-way factorial designs: All of these designs can involve any combination of manipulated IVs and/or selected IVs All of these ANOVA models have 3 F-tests one for each of two Main Effects and one for the Interaction

BETWEEN GROUPS FACTORIAL DESIGN: both of the IVs use between groups comparison each participant completes only one condition of the design WITHIN-GROUPS FACTORIAL DESIGN: both of the IVs use within-groups comparison each participant completes all conditions of the design MIXED FACTORIAL DESIGN: one of the IVs uses a between groups comparison and one of the IVs uses a within-groups comparison. each participant completes both conditions of the within- groups IV, but completes only one condition of the between groups IV. it is important to specify which IV uses a between groups comparison and which IV uses a within-groups comparison

Between groups factorial design -- Each participant is in only one condition, having a particular combination of Initial Diagnosis and Type of Treatment. Type of Treatment Initial Diagnosis Individual Group Therapy Therapy Clients diagnosed Clients diagnosed Depression as depressed who as depressed who are treated with are treated with individual therapy group therapy Clients diagnosed Clients diagnosed Social Anxiety with social anxiety with social anxiety who are treated with who are treated with individual therapy group therapy

Mixed group factorial design Species was a between groups IV (a turtle can only be a member of one species). Each turtle participated in both the mid-morming & dusk conditions of the Time of Day IV. Species of Turtle Time of Day Snapping Turtle Painted Turtle Each snapping turtle Each painted turtle Mid-morning completed a trial completed a trial during mid-morning during mid-morning Each snapping turtle Each painted turtle Evening completed a trial completed a trial during the evening during the evening

Within-groups factorial design -- Each participant completed four trials, one of each combination of Retention Interval and Word Type. Retention Interval Word Type Immediate Test Delayed Test The test was given The test was given Familiar immediately after the 5 minutes after the study of a list of study of a list of 40 familiar words. 40 familiar words. The test was given The test was given Unfamiliar immediately after the 5 minutes after the study of a list of study of a list of 40 unfamiliar words. 40 unfamiliar words.

Practice Identifying Types of Factorial Designs - answers next page The purpose of the study was to examine the possible influence of two variables upon maze-learning by rats, length of the maze (either 10 feet or 30 feet) and the size of the reward (either 1sugar pellet or 5 sugar pellets). Here are three “versions” of the study tell which is BG, WG & MG a. Each rat completed one trial. Each was assigned to either the longer or the shorter maze, and also assigned to receive either 1 or 5 sugar pellets upon completing the maze. b. Each rat completed two trials in either the longer or the shorter maze. Following one trial in the assigned maze, each received 1 pellet reward, after the other trial they received the 5 pellets. c. Each rat completed four trials, two in the shorter maze and two in the longer maze. Each received 1 pellet after one of the short-maze trials and 5 pellets after the other, and also 1 pellet after one of the long-maze trials and 5 pellets after the other. BG MG WG

Another Example -- 3 versions of the same study The researcher wanted to investigate infant's startle responses to loud sounds. The two variables of interest were the Position of the Sound (in front of versus behind the infant) and the Type of Sound (a hand-clap versus deep male voice saying "Hey"). Here are three “versions” of the study tell which is BG, WG & MG a. Each infant completed trials all involving a hand-clap or all involving the voice saying "Hey". During some of the trials, the appropriate type of sound was made in front of the infant. During other trials, the appropriate type of sound was made behind the infant. b. Each infant had some trials during which the sound was made in front of then and some during which the sound was made behind them. Some of the sounds were the hand-clap and the others were the voice saying "Hey". c. Each infant always heard either the hand-clap or the “Hey”, and whatever sound they heard was always played either in front of them or behind them. BG MG WG

Remember about the causal interpretation of effects of a factorial design Start by assessing the causal interpretability of each main effect Remember, in order to causally interpret an interaction, you must be able to casually interpret BOTH main effects. For each of the following: Tell the IVs and tell what effects could be causally interpreted (assuming proper RA, IV manip. and confound control were used): 1. Male and female participants who were African American, Mexican American, or European American were asked to complete a questionnaire about satisfaction with their Senators. 2. Children played with either a toy gun, a toy car or a puzzle, some while their parents were in the room and some not. The DV was the amount of aggressive behavior they exhibited. 3. Participants played with either a simple puzzle or a complex puzzle in pairs made up of two boys, two girls or one boy & one girl. zilcho-causo Puzzle type only. All three !

F-tests of the BG Factorial Designs SS total = SS A + SS B + SS INT + SS Error df total = df A + df B + df INT + df Error (N - 1) = ( a -1) + (b-1) + (a-1)(b-1) + ab(n-1) SS A / df A SS B / df B SS INT / df INT F A = F B = F INT = SS E / df E SS E / df E SS E / df E Things to notice: There is a single error term that is used for all the Fs All of the effects are “equally powerful” (all use same sample size -- power depends upon sample size)

F-tests of the MG Factorial Designs SS total = SS A + SS S/A + SS B + SS INT + SS BxS/A df total = df A + df S/A + df B + df INT + df BxS/A (N - 1) = (a -1) + a(S-1) + (b-1) + (a-1)(b-1) + b(S-1) SS A / df A SS B / df B SS INT / df INT F A = F B = F INT = SS S/A / df S/A SS BxS/A / df BxS/A SS BxS/A / df bxS/A Things to notice: There are two error terms -- one for the BG main effect and another for the WG main effect and the interaction The WG ME test and the interaction are usually more powerful, than the BG ME BG main effect is less powerful in this design than for BG design

F-tests of the WG Factorial Designs SS total = SS Sub + SS A + SS SxA + SS B + SS SxB + SS INT + SS SxI df total = df Sub + df A + df SxA + df B + df SxB + df INT + df SxI (N - 1) = (S-1) + (a -1)+(S-1)(a-1) + (b-1)+(S-1)(b-1) + (a-1)(b-1)+(S-1)(a-1)(b-1) SS A / df A SS B / df B SS INT / df INT F A = F B = F INT = SS SxA / df SxA SS SxB / df SxB SS SxINT / df SxINT Things to notice: There is a separate error term that is used for each F These tests are about equally powerful as the WG effects of the MG design, and more powerful than the BG effects of the other

LSD Follow-ups As for the BG factorials, any design larger than a 2x2 will require follow-up analyses cell and/or marginal means Main Effects any significant ME with more than 2 conditions will require follow-ups to describe the pattern of marginal means follow-up of the corresponding simple effects will be required to determine if that ME is descriptive or potentially misleading LSDs use the error term specific to that ME F-test Interaction the LSD minimum mean difference can be used for either 2- or k-condition simple effects, to describe the pattern LSD uses WG error term from the interaction F-test