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Roadmap: Stroop

Overview:

Lab 2 introduces you to the nuts and bolts of another classic experimental psychology paradigm, the Stroop effect. Data collection will occur on the computers. Each student will complete a 20-30 minute Stroop experiment. The data will be analyzed and reported in a full APA style research report.

The main goal of this experiment is provide a concrete example of a 2×2 Factorial Design. As well, we will learn to relate theory and data.You will be taught about the horse-race model of Stroop, and you will use this model to predict the data from the class experiment.

The class experiment has two goals. First, to replicate the Stroop effect. Second, to test a manipulation that will reduce the size of the Stroop effect. In this case, the manipulation will be task. For half of the trials, you will identify the color, and for the other half of the trials you will identify the word.

In your research paper you will be required to introduce the Stroop effect, and explain the horse race model. You will explain how the horse race model can be used to predict which task will lead to the largest Stroop effect. You will describe the methods and results. The results will be reported in a figure or table (your choice).

NOTE: when you report the results you MUST report all main effects, the interaction, and any necessary post-hoc tests.

Things you will learn:

Using reaction time as a dependent measure 2×2 Factorial designs Reading and citing primary source material Predicting data based on a theory

Control in experimental design Background on the Stroop paradigm:

The Stroop paradigm involves the identification of a bi-valent stimulus. For example, you could be presented with a word, that is written in a particular color. Dimension 1 is the word (e.g., BLUE), and dimension 2 is the color (e.g., RED). The resulting stimulus would look like this: BLUE. In this case the word and color do not match, this is called an incongruent stimulus. A congruent stimulus occurs when the word and color dimension match (e.g., BLUE). In a standard Stroop experiment you would be presented with these kinds of congruent and incongruent items. The task usually involves identifying the color dimension as quickly as possible, while ignoring the word. The Stroop effect itself is the finding that reaction times to identify the color dimension are faster for congruent trials (when the word matches) than incongruent trials (when the word mismatches). The effect is interesting because people are unable to ignore the word dimension even though it is not part of their task. The Stroop effect is usually used to measure your ability to selectively attend to information in your environment. The review paper by Macleod (1990) demonstrates the popularity of Stroop research, and the many different ways that this task has already been studied.

Background readings:

Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643-662.

Macleod, C. M. (1991). Half a century of research on the Stroop effect: An integrative review. Psychological Bulletin, 109, 163-203.

-Pages 187-188 describe the horse-race model (it is termed the relative speed of processing account).

Writing the paper

Refer to the lab manual for more resources on writing APA style research-reports.

1. Use the same general APA formatting rules that you learned in lab 1. 2. Create a suitable title for the paper 3. Write the abstract :

-no more than 150 words

-The aim is to very briefly describe the main experimental aims, how they address the theory at hand, and the basic pattern of results.

The introduction (around 2 double-spaced pages)

The goal of the introduction is to put the research into a broader context, and then narrow the focus to describe the specific research aims.

A. Opening section: (starting broad) – about 1 paragraph

-Define the general problem of selective attention.

-Give an anecdote that describes a real-world situation involving the need to select task- relevant from irrelevant information

-Link this real world situation to the Stroop paradigm (this provides an argument that the Stroop paradigm can be used to understand how selective attention works

B. Middle section: (discussing prior work)

-Define the Stroop paradigm (1-2 paragraphs) -cite the original paper

 

-describe the basic features of a Stroop experiment -Describe the assumptions of the Horse-Race model (1-2 paragraphs)

 

-e.g., the model assumes color and word information have different processing times -Mention that the purpose of the experiment is to test predictions of the model.

 

C. Final section: (narrowing down to the aims of the experiment) -Explain that the specific aim of the experiment is to further test the horse-race model of the

 

Stroop effect. -Briefly describe the independent variables that will be manipulated

 

-Congruency (congruent vs. incongruent

 

-Task (name color vs. name word) -Does the model predict a main effect of Congruency? -Does the model predict a main effect of Task? -Does the model predict an interaction between Congruency & Task?

 

Methods (1-2 pages)

 

The methods section should be a complete recipe that anyone could follow to replicate your experiment. At the same time, you should be as brief as possible.

 

-Participants -how many people? where did they come from?

 

– Materials -How many words, how many colors -How were they combined to make congruent and incongruent items

 

-How many congruent items -how many incongruent items

 

-Procedure -What was the design, IVS, DVs, within or between? -how many trials -how were the stimuli for each trial chosen -Describe the complete trial-sequence

 

-first the fixation cross appeared (for how long) -then the Stroop stimulus appeared (for how long) -reaction times were recorded

 

6. Results

 

The result section is used to report the patterns in the data, and the statistical support for those patterns. Refer to the lab manual for help on reporting statistics from a factorial design. – Describe the statistical analysis

 

e.g., mean RTs from each condition were submitted to a 2(Task:name word vs. color) x 2 (congruency: congruent vs. incongruent) within-subjects ANOVA. -Tell the reader where they can see the data.

 

-e.g., the results of experiment 1 are presented in table 1, or in figure 1 -you will have to make a table or figure to display the data in your paper

 

-Describe the pattern of each main effect -The main effect of Task was … -The main effect of Congruency was …

 

-Describe the Congruency X Task interaction -You will report the interaction the same way as a main effect.

 

7. Discussion

 

The discussion can be used to briefly restate verbally the pattern of the most important results, and then to relate the results to theory and ideas developed in the introduction

 

-highlight the main findings from the experiment -remind the reader that the point of the paper is to evaluate predictions from the model -discuss whether or not the model accurately predicted the patterns of data.

 

8. References

 

-include citations used in the paper

 

9. figures or tables

 

METHODS OF EXPERIMENT CONDUCTED … GOES INTO THE METHODS SECTION

 

Stroop Fact Sheet

 

Computer details

 

– The experiment was conducted on PCs running in-house METACARD software.

 

– The screens were 15″ LCD

 

Stimulus details

 

Number of words used – 4 (red, green, blue, yellow) Number of colors used – 4 (red, green, blue yellow)

 

Each Stroop stimulus involved the presentation of one color and one word. The word and color were presented simultaneously

 

Independent variables

 

Congruency Number of possible congruent items – 4 Number of possible incongruent items – 12 proportion of congruent and incongruent trials – 50/50

 

Task 1 block of 48 trials: Name the word 1 block of 48 trials: Name the color 96 total trials

 

The order of each block was randomly determined by the computer for each subject. Half of the subject will do word naming then color naming. The other half will do color naming then word naming

 

Design

 

The experiment involved the factorial combination of 2 independent variables, each with 2 separate levels in a within-subjects design. In other words, the design was 2 (Congruency: congruent vs. incongruent) x 2 (Task: name word vs. color)

 

This means that all subjects experienced an equal number of trials representing each of the independent variables. This is how each trial breaks down.

 

Responses

 

There are four possible responses: red, green, blue, & yellow. Responses are given by having subjects type the word into the computer keyboard.

 

Details of a single trial

 

-Each trial begins with the presentation of a fixation cross in the center of the screen -the fixation cross is visible for 500 milliseconds -the fixation cross is removed, and immediately followed by the word and color stimulus -The stroop stimulus remained on the screen until a response was typed and the participant pressed the spacebar

 

-Immediately after the response the stimuli were removed from the screen -the next trial was triggered 500 milliseconds after the last keypress

 

EXCEL FILE AND SPPS FILE GOES INTO RESULTS SECTION … INTERPRET THESE NUMBERS INTO WORDS … THE MEANS AND STANDARD DEVIATIONS

 

Name Color Name Word
Congruent Incongruent Congruent Incongruent
Macintosh HD:Users:mook:Library:Caches:TemporaryItems:msoclip:0:clip_image001.png
Macintosh HD:Users:mook:Library:Caches:TemporaryItems:msoclip:0:clip_image002.png
1,1 1,2 2,1 2,2
1083 1503 847 979
1285 1412 980 1090
1539 1648 971 970 name color name word
1415 1682 1234 1155 congruent 1129.26 834.16
854 1200 629 618 incongruent 1327.00 879.68
1142 1397 728 813 ERROR
988 1275 882 933 name color name word
978 1091 772 791 congruent 202.15 137.75
1441 1487 855 968 incongruent 203.31 151.48
1024 1071 879 1119
1008 1196 808 722
1364 1646 907 945
985 1167 682 800
1093 1322 764 731
987 1161 812 841
1078 1348 799 786
1312 1443 857 933
1020 1074 816 876
860 1090 627 644
1129.26 1327.00 834.16 879.68 MEANS
202.15 203.31 137.75 151.48 STDEV

 

SPSS FILE

 

Descriptive Statistics
Mean Std. Deviation N
Cong_Color 1129.2632 202.15309 19
Incog_Color 1327.0000 203.30738 19
Cong_Word 834.1579 137.74948 19
Incong_Word 879.6842 151.47792 19

 

Multivariate Testsa
Effect Value F Hypothesis df Error df Sig. Partial Eta Squared
Color Pillai’s Trace .876 127.106b 1.000 18.000 .000 .876
Wilks’ Lambda .124 127.106b 1.000 18.000 .000 .876
Hotelling’s Trace 7.061 127.106b 1.000 18.000 .000 .876
Roy’s Largest Root 7.061 127.106b 1.000 18.000 .000 .876
Word Pillai’s Trace .839 93.700b 1.000 18.000 .000 .839
Wilks’ Lambda .161 93.700b 1.000 18.000 .000 .839
Hotelling’s Trace 5.206 93.700b 1.000 18.000 .000 .839
Roy’s Largest Root 5.206 93.700b 1.000 18.000 .000 .839
Color * Word Pillai’s Trace .527 20.091b 1.000 18.000 .000 .527
Wilks’ Lambda .473 20.091b 1.000 18.000 .000 .527
Hotelling’s Trace 1.116 20.091b 1.000 18.000 .000 .527
Roy’s Largest Root 1.116 20.091b 1.000 18.000 .000 .527
a. Design: Intercept

Within Subjects Design: Color + Word + Color * Word

b. Exact statistic

 

Mauchly’s Test of Sphericitya
Measure: RT
Within Subjects Effect Mauchly’s W Approx. Chi-Square df Sig. Epsilonb
Greenhouse-Geisser Huynh-Feldt Lower-bound
Color 1.000 .000 0 . 1.000 1.000 1.000
Word 1.000 .000 0 . 1.000 1.000 1.000
Color * Word 1.000 .000 0 . 1.000 1.000 1.000
Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix.
a. Design: Intercept

Within Subjects Design: Color + Word + Color * Word

b. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table.

 

Tests of Within-Subjects Effects
Measure: RT
Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared
Color Sphericity Assumed 2618147.842 1 2618147.842 127.106 .000 .876
Greenhouse-Geisser 2618147.842 1.000 2618147.842 127.106 .000 .876
Huynh-Feldt 2618147.842 1.000 2618147.842 127.106 .000 .876
Lower-bound 2618147.842 1.000 2618147.842 127.106 .000 .876
Error(Color) Sphericity Assumed 370765.158 18 20598.064
Greenhouse-Geisser 370765.158 18.000 20598.064
Huynh-Feldt 370765.158 18.000 20598.064
Lower-bound 370765.158 18.000 20598.064
Word Sphericity Assumed 281090.579 1 281090.579 93.700 .000 .839
Greenhouse-Geisser 281090.579 1.000 281090.579 93.700 .000 .839
Huynh-Feldt 281090.579 1.000 281090.579 93.700 .000 .839
Lower-bound 281090.579 1.000 281090.579 93.700 .000 .839
Error(Word) Sphericity Assumed 53998.421 18 2999.912
Greenhouse-Geisser 53998.421 18.000 2999.912
Huynh-Feldt 53998.421 18.000 2999.912
Lower-bound 53998.421 18.000 2999.912
Color * Word Sphericity Assumed 110048.211 1 110048.211 20.091 .000 .527
Greenhouse-Geisser 110048.211 1.000 110048.211 20.091 .000 .527
Huynh-Feldt 110048.211 1.000 110048.211 20.091 .000 .527
Lower-bound 110048.211 1.000 110048.211 20.091 .000 .527
Error(Color*Word) Sphericity Assumed 98592.789 18 5477.377
Greenhouse-Geisser 98592.789 18.000 5477.377
Huynh-Feldt 98592.789 18.000 5477.377
Lower-bound 98592.789 18.000 5477.377

 

Tests of Within-Subjects Contrasts
Measure: RT
Source Color Word Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared
Color Linear 2618147.842 1 2618147.842 127.106 .000 .876
Error(Color) Linear 370765.158 18 20598.064
Word Linear 281090.579 1 281090.579 93.700 .000 .839
Error(Word) Linear 53998.421 18 2999.912
Color * Word Linear Linear 110048.211 1 110048.211 20.091 .000 .527
Error(Color*Word) Linear Linear 98592.789 18 5477.377

 

Estimates
Measure: RT
Color Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1228.132 44.963 1133.669 1322.595
2 856.921 31.962 789.770 924.072

 

Pairwise Comparisons
Measure: RT
(I) Color (J) Color Mean Difference (I-J) Std. Error Sig.b 95% Confidence Interval for Differenceb
Lower Bound Upper Bound
1 2 371.211* 32.926 .000 302.036 440.385
2 1 -371.211* 32.926 .000 -440.385 -302.036
Based on estimated marginal means
*. The mean difference is significant at the .05 level.
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).

 

Multivariate Tests
Value F Hypothesis df Error df Sig. Partial Eta Squared
Pillai’s trace .876 127.106a 1.000 18.000 .000 .876
Wilks’ lambda .124 127.106a 1.000 18.000 .000 .876
Hotelling’s trace 7.061 127.106a 1.000 18.000 .000 .876
Roy’s largest root 7.061 127.106a 1.000 18.000 .000 .876
Each F tests the multivariate effect of Color. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic

 

WORD

 

Estimates
Measure: RT
Word Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 981.711 36.318 905.409 1058.012
2 1103.342 35.512 1028.734 1177.950

 

Pairwise Comparisons
Measure: RT
(I) Word (J) Word Mean Difference (I-J) Std. Error Sig.b 95% Confidence Interval for Differenceb
Lower Bound Upper Bound
1 2 -121.632* 12.565 .000 -148.031 -95.233
2 1 121.632* 12.565 .000 95.233 148.031
Based on estimated marginal means
*. The mean difference is significant at the .05 level.
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).

 

Multivariate Tests
Value F Hypothesis df Error df Sig. Partial Eta Squared
Pillai’s trace .839 93.700a 1.000 18.000 .000 .839
Wilks’ lambda .161 93.700a 1.000 18.000 .000 .839
Hotelling’s trace 5.206 93.700a 1.000 18.000 .000 .839
Roy’s largest root 5.206 93.700a 1.000 18.000 .000 .839
Each F tests the multivariate effect of Word. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic

 

3. Color * Word
Measure: RT
Color Word Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 1129.263 46.377 1031.828 1226.698
2 1327.000 46.642 1229.009 1424.991
2 1 834.158 31.602 767.765 900.551
2 879.684 34.751 806.674 952.694

 

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