CHAPTER 3: METHODOLOGY
3.4 Data Analysis
All the data collected was organised into Excel tables. The data set comprised of an experimental (n = 13) and a control group (n = 13). Namely, an ASD group of participants and a Non-ASD group of participants. Some data was nominal data and some interval data.
3.4.1 Gender and ethnicity in the sample
Descriptive analysis of the sample (n = 26) considering the percentages represented by gender and ethnicity, were calculated. Patterns that emerged in the data were represented in pie charts.
3.4.2 Concordant diagnoses
The comparison of the concordant diagnostic ability of the ADOS diagnoses per participant, andthat of the trained clinician diagnoses were recorded as nominal, dichotomous data.
3.4.1.2 Descriptive statistics
Initially graphs were drawn using Excel to observe whether concordance between the diagnoses could be visually made.
3.4.1.3 Statistical analyses
Further, comparisons were made using a specialised version of McNemar’s Test called the Westlake-Schuirmann Test of Equivalence for two dependent samples. The McNemar’s inferential statistic is used with nominal or categorical data when evaluating a hypothesis about the distribution of data into two dependent populations (Sheskin, 2007).
The Westlake-Schuirmann Test, an equivalence testing hypothesis as opposed to the zero- difference hypothesis used in analysis of variance (ANOVA), was also used in this study.
The aim of using this test was to see whether two dependent samples represent different populations. It aims to evaluate whether the ADOS diagnoses of the 26 participants is
equivalent to the clinical diagnoses given to each of these 26 participants. The McNemar Test (McNemar, 1947) is a nonparametric procedure for categorical data employed in a hypothesis testing situation like this study, where the design comprises two dependent samples.
In this sample (n) of matched subjects, a dichotomous (Yes=1/No=0) dependent variable is used. Where Yes=1 shows that a person has ASD and No=0 means that they do not have ASD. A significant result allows the researcher to conclude that there is a high likelihood that the two groups represent two different populations.
The McNemar Test is based on the following assumptions:
1. The sample of n subjects has been randomly selected from the group that it represents (Due to time constraints children with or without ASD were selected from special needs schools willing to participate in the study. They were blindly assigned to the researcher so they never knew the clinical diagnosis of each participant when the ADOS was administered to them)
2. Each of the n observations in the contingency table are independent of all other observations (Each child was individually assessed independently of other observations).
3. The scores of the subjects are in the form of dichotomous categorical measures involving two mutually exclusive categories.
4. Most sources state that McNemar’s Test should not be employed with extremely small sample sizes (Sheskin, 2007). Due to the small sample size in this study, some sources recommend the use of a correction for continuity (Sheskin, 2007). This shall be done to counter the fact that n=26.
3.4.3 ADOS sub-category analyses
The ADOS sub-categories of each group were also compared according to ethnicity and scores were entered as numerical values. The sub-categories were:
Communication
Reciprocal Social Interaction
Imagination/creativity
Stereotyped behaviours/ restricted interests
Thus, each ethnic group was compared on each algorithm to note whether diagnosis on the ADOS varied across ethnic lines. Hypotheses were formulated in this regard (see page 43 and 44 of this thesis).
3.4.3.1 Statistical analyses
For all statistical decisions made in this study, an alpha level of p = 0.05 was used.
The different ethnicity scores across all ADOS sub-categories were compared using one-way analyses of variance (ANOVA), to observe whether there was a systematic difference was present in the sample (Durrheim, 2002). In this regard the specific question was ‘Do variable ethnic groups within the sample responded differently to the ADOS sub-categories in a statistically significant manner? ‘This one-way ANOVA was a suitable design for this study as it comprised one categorical independent variable, ethnicity, which had three distinct categories (Black, White and Indian) and one continuous variable which is ADOS scores on each sub-category (Pallant, 2001).
A Levene’s Test was initially run to test for homogeneity of variance, as the populations from which the data was sampled should have the same variance. This was one of the assumptions of an ANOVA (Sheskin, 2007; Durrheim, 2002). The other assumption was that populations represented by the data should be normally distributed (Sheskin, 2007; Durrheim, 2002).
An F-statistic was then calculated and if significant, a systematic difference was found.
Which means that the null hypothesis stating equal means between groups could be rejected (Durrheim, 2002). This meant that the ethnic groups responded differently to the ADOS in a significant manner as the scores on the sub-categories varied significantly from each other.
Post-hoc tests were used to reveal where the significant patterns of difference between ethnic groups lay (Durrheim, 2002). They systematically compare each ethnic group to another, in pairs, to indicate whether there is a significant difference in the means of each (Pallant, 2001). More specifically it indicated the sub-categories on which the ethnic groups varied significantly (Pallant, 2001).
3.4.4. Analysis of personal files
After the ADOS had been administered to the whole sample and scores had been completed, the personal files of each participant on the study were analysed by a trained clinician. The comorbid factors and other variables were also recorded as Yes/No, dichotomous data. The race variable was coded categorically as Black = 1, White = 2, Indian = 3.
For each participant tested on the ADOS, the following data was extracted from their personal files kept at the schools and transcribed in a spread sheet format using Excel:
Race
Home language
Date of Birth
Gender
ADOS Module administered
Subtest algorithm scores on the ADOS o Communication
o Reciprocal Social Interaction o Imagination and Creativity
o Stereotyped behaviours/ repetitive Interests o Diagnosis ASD/Non-ASD
Speech and Language delays
Mental retardation
ADHD
Neurodevelopmental disorders
Hearing Impairment
Pre-birth and congenital history
Early and middle childhood developmental difficulties
Pervasive developmental disorders
Oppositional defiance disorders
Aggression
Sexual abuse
3.4.4.1 Descriptive statistics
The information from the personal files were analysed and compared considering patterns that emerged in the data. The frequencies of Mental retardation, ADHD and other comorbid factors with ASDs were noted. Percentages were calculated and presented in a bar graph.