Lecturer: A.Prof Peter Wilson

Paul Emerson s3104960 Research Methods in Psychology BESC1449 Lab_04 Time: 1530-1730 Lecturer: A.Prof Peter Wilson Tutor: Gamze Due date: 16 April 2009

Data Analysis Assignment

Results were analysed using SPSS for Windows statistical package, version 17.0

Q1) What type of research design best describes the comparison on EEG activity?

Explain your answer.

The type of research design that best describes the comparison on EEG activity is the Quasi-Experimental Method as group assignment has already taken place and the values of the independent variable are there to begin with, such as gender, age and illness.

Q2) Comment briefly on the main variables that might need to be controlled for when making group comparisons here.

The main variables that might need to be controlled for when making group comparisons here are socio-economic status, gender, age, time of day the tests are conducted in relation to one's circadian rhythm, along with the possibility of participants engaging in any of the following treatments (e.g., clinical therapy, methylphenidate and parenting programs such as Systematic training for effective parenting, Parent effective training and Positive parenting programme).

Q3) For the Control group only, present a histogram that shows the distribution of scores for EEG activity. Comment on whether this plot appears to be normally distributed.

Figure 1. Distribution of scores for EEG activity for typically developing children.

As shown in Figure 1, the plot was not normally distributed, but rather it was skewed left indicating few low values as most of the data was concentrated on the right-hand side of the figure. This was further underpinned by the result in Table 1 that showed a skewness of -.607.

2 Q4) Generate descriptive statistics (means and standard deviations) for each group

and the total sample on EEG activity and verbal ability. Present these results using

APA style, incorporating a table.

Table 1

Ranges, Means, Standard Deviations and Skewness for EEG activity and verbal

ability for each group

Std. N Range Mean Deviation Skewness group Statistic Statistic Statistic Statistic Statistic Std. Error ADHD EEG activity level over 20 3.30 1.9700 .99689 .201 .512 prefrontal cortex Verbal ability 20 4.00 7.3300 1.24355 -.366 .512 Valid N (listwise) 20 Autism EEG activity level over 20 3.80 1.8850 .95271 .629 .512 prefrontal cortex Verbal ability 20 6.00 5.9750 1.85752 -.766 .512 Valid N (listwise) 20 Control EEG activity level over 20 4.50 3.2200 1.37366 -.607 .512 prefrontal cortex Verbal ability 20 6.20 10.3150 1.73305 -.397 .512 Valid N (listwise) 20

3 Table 2

Ranges, Means, Standard Deviations and Skewness for EEG activity and verbal

ability for the total sample

N Range Mean Std. Deviation Skewness

Statistic Statistic Statistic Statistic Statistic Std. Error

EEG activity level over 60 5.00 2.3583 1.26441 .360 .309 prefrontal cortex

Verbal ability 60 11.00 7.8733 2.43289 .020 .309

Valid N (listwise) 60

The total sample comprised 30 females and 30 males. Table 1 shows measures

of central tendency and variability of each group, while Table 2 shows the measures

of central tendency and variations of the total sample.

Typically developing children scored higher on EEG activity (M = 3.22, SD =

1.37) compared to children with ADHD (M = 1.97, SD = 1) and autistic children (M =

1.89, SD = 0.95). In addition, typically developing children scored higher on verbal

ability (M = 10.32, SD = 1.73) compared to those children with ADHD (M = 7.33, SD

= 1.24) and autistic children (M = 5.98, SD = 1.86). Interestingly, typically developing

children scored slightly higher on verbal ability (M = 10.32, SD = 1.73) compared to

the population. (M = 10, SD = 3).

When you look at the means for each group, it appears the greater the degree

of EEG activity level over the prefrontal cortex, the greater the child’s verbal ability.

4 This in part could be explained by typically developing children possessing a larger prefrontal cortex and brain stem compared to either ADHD or autistic children.

Q5) Present a bar chart (in APA style) that compares the performance of the three groups on EEG activity. Comment on the apparent differences between groups.

Figure 2. Distribution of the performances of each group on EEG activity.

Figure 2 shows mean EEG activity over the prefrontal cortex for each of the groups during performance of the Stroop Test and indicated negligible difference between children with either ADHD or autism. In contrast, typically developing children scored a significantly higher mean EEG activity which may be due in part to typically developing children having a larger prefrontal cortex and brain stem.

5 Q6) Tabulate changes in mean levels of maladaptive behaviour for each group.

Present these results in APA style and comment on the pattern of group differences.

(A bonus mark for anyone who can present these results using a 2-way plot).

Table 3

Changes in Means and Standard Deviations of maladaptive behaviour at four points over a 1-year period for each group and the total sample

Std. group Mean Deviation N Level of maladaptive ADHD 7.3650 1.00277 20 behaviour - time 1 Autism 7.1650 1.24236 20 (baseline) Control 3.3350 .57790 20 Total 5.9550 2.10370 60 Level of maladaptive ADHD 4.7550 1.10476 20 behaviour - time 2 Autism 5.3350 .80673 20 Control 3.5850 1.33625 20 Total 4.5583 1.31010 60 Level of maladaptive ADHD 2.2550 .65331 20 behaviour - time 3 Autism 3.3600 .67231 20 Control 3.2750 .41660 20 Total 2.9633 .77152 60 Level of maladaptive ADHD 2.5650 .84497 20 behaviour - time 4 Autism 2.6200 .60750 20 Control 2.7800 .99292 20 Total 2.6550 .82141 60

6 Figure 3. A 2-way plot representing changes in Means and Standard Deviations of

maladaptive behaviour at four points over a 1-year period for each group.

The Parents of participants from each group completed a questionnaire which tracked changes in mean maladaptive behaviour at four points over a 1-year period. A general linear model of repeated measures was used to compute and thence examine any developmental change. The highest level of mean maladaptive behaviour was recorded during the first of the four periods for children with ADHD (M = 7.37). In contrast, the lowest level of mean maladaptive behaviour was recorded during the third period, also for children with ADHD (M = 2.26). Overall, there was decrease in maladaptive behaviour for ADHD and autistic children, however typically developing children retained a relatively constant, low level of maladaptive behaviour.

7 The change in maladaptive behaviour may have been due to issues relating to internal or external validity, or a combination of both, and given this was a study based on the implementation of the Quasi-Experimental Method, a lack of randomization may have posed a threat to internal validity.

Q7) For each group, calculate the correlation between EEG activity and verbal ability. Present a scatterplot showing this relationship in each group. Comment on whether there appear to be any outliers (hint: for one of the groups, this does appear to be the case). For the group in question, remove the obvious outlier/s and re- calculate the correlation (citing the subject number removed). Present all these results in APA style.

Table 4

Means and Standard Deviations for EEG activity and verbal ability for each group

group Mean Std. Deviation N

ADHD EEG activity level over 1.9700 .99689 20 prefrontal cortex

Verbal ability 7.3300 1.24355 20

Autism EEG activity level over 1.8850 .95271 20 prefrontal cortex

Control EEG activity level over 3.2200 1.37366 20 prefrontal cortex

Verbal ability 10.3150 1.73305 20

8 Table 5

Correlations of EEG activity and verbal ability for each group (N = 60)

EEG activity level over prefrontal Verbal group cortex ability ADHD EEG activity level over Pearson 1 .717** prefrontal cortex Correlation Sig. (2-tailed) .000 N 20 20 Verbal ability Pearson .717** 1 Correlation Sig. (2-tailed) .000 N 20 20 Autism EEG activity level over Pearson 1 -.002 prefrontal cortex Correlation Sig. (2-tailed) .994 N 20 20 Verbal ability Pearson -.002 1 Correlation Sig. (2-tailed) .994 N 20 20 Control EEG activity level over Pearson 1 .309 prefrontal cortex Correlation Sig. (2-tailed) .185 N 20 20 Verbal ability Pearson .309 1 Correlation Sig. (2-tailed) .185 N 20 20

**. Correlation is significant at the 0.01 level (2-tailed).

9 Figure 4. Relationship between EEG activity and verbal ability for children with

10 Figure 5. Relationship between EEG activity and verbal ability across children with

autism.

11 Figure 6. Relationship between EEG activity and verbal ability across typically

developing children.

A Pearson product-moment correlation coefficient was computed to assess the relationship between EEG activity and verbal ability for each group (Table 5). There was a positive correlation between the two variables for children with ADHD, r(n =

20) = .72, p < .01, |r| = .52 (2-tailed). A scatterplot summarizes the results (Figure 4).

Overall, there was a strong, positive, significant correlation between EEG activity and verbal ability. Increases in EEG activity were correlated with increases in verbal ability for children with ADHD.

12 There was a negative correlation between the two variables for children with autism, r(n = 20) = -.002, p > .05, |r| = .000004 (2-tailed). A scatterplot summarizes the results (Figure 5). Overall, there was a very weak, negative, non-significant correlation between EEG activity and verbal ability. Increases in EEG activity were correlated with slight decreases in verbal ability for children with autism.

There was a positive correlation between the two variables for typically developing children, r(n =20) = .309, p > .05, |r| = .095 (2-tailed). A scatterplot summarizes the results (Figure 6). Overall, there was a weak, positive, non-significant correlation between EEG activity and verbal ability. Increases in EEG activity were correlated with increases in verbal ability for typically developing children.

Table 6

Means and Standard Deviations for EEG activity and verbal ability for each group

group Mean Std. Deviation N

ADHD EEG activity level over 1.9700 .99689 20 prefrontal cortex

Autism EEG activity level over 1.9706 .99358 17 prefrontal cortex

Control EEG activity level over 3.1158 1.32760 19 prefrontal cortex

Verbal ability 10.4632 1.64527 19

13 Table 7

Correlations of EEG activity and verbal ability for each group post removal of relevant outliers (N = 56)

EEG activity level over prefrontal group cortex Verbal ability

** ADHD EEG activity level over Pearson Correlation 1 .717 prefrontal cortex Sig. (2-tailed) .000 N 20 20 Verbal ability Pearson Correlation .717** 1 Sig. (2-tailed) .000 N 20 20

Autism EEG activity level over Pearson Correlation 1 -.234 prefrontal cortex Sig. (2-tailed) .365 N 17 17 Verbal ability Pearson Correlation -.234 1 Sig. (2-tailed) .365 N 17 17 * Control EEG activity level over Pearson Correlation 1 .505 prefrontal cortex Sig. (2-tailed) .028 N 19 19 Verbal ability Pearson Correlation .505* 1 Sig. (2-tailed) .028 N 19 19

**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

14 Figure 7. Relationship between EEG activity and verbal ability across autistic

children post removal of three data points.

15 Figure 8. Relationship between EEG activity and verbal ability across typically

developing children post removal of one data point.

Z-scores were computed for raw scores for EEG activity and verbal ability.

There were four z-scores which told us that participants (25, 44 and 51) scored below the relevant group average for verbal ability, and participant (five) scored below the relevant group average for verbal ability, while simultaneously, scoring above the group average for EEG activity over the prefrontal cortex. After removing the four relevant outliers, a second Pearson product-moment correlation coefficient was computed to assess the relationship between EEG activity and verbal ability for each group (Table 7).

16 There was a negative correlation between the two variables for autistic children, r(n = 17) = -.23, p > .05, |r| = .055 (2-tailed). A scatterplot summarizes the results (Figure 7). Overall, there was a weak, negative, non-significant correlation between EEG activity and verbal ability. Increases in EEG activity were correlated with decreases in verbal ability for autistic children.

There was a positive correlation between the two variables for typically developing children, r(n = 19) = .51, p < .05, |r| = .26 (2-tailed). A scatterplot summarizes the results (Figure 8). Overall, there was a moderate, positive, significant correlation between EEG activity and verbal ability. Increases in EEG activity were correlated with increases in verbal ability for typically developing children.

17 Q8) For the total sample, present descriptive results that compare males and females

on verbal activity. Do this using APA style and comment on whether there appears to

be a gender difference.

Table 8

Ranges, Means, Standard Deviations and Skewness for males and females

Std. N Range Mean Deviation Skewness Gender Statistic Statistic Statistic Statistic Statistic Std. Error male Verbal ability 30 7.10 8.0800 1.80772 .090 .427 Valid N 30 (listwise) female Verbal ability 30 11.00 7.6667 2.94716 .144 .427 Valid N 30 (listwise)

Table 8 highlights a difference between genders on verbal ability that was measured by testing the participant’s vocabulary. Males scored a higher mean level (M = 8.08) compared to females (M = 7.67). However, females scored a higher range (R = 11) compared to males (R = 7.1), indicating that some female participants recorded lower minimum and higher maximum scores compared to male participants (Figure 9).

18 Figure 9. Distribution of verbal ability scores across gender.

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