Chapter 4 Timeliness of Financial Reporting and Audit Delay
5.8 Data Analyses
Reliability analysis is one of the first steps a researcher has to undertake for quality control when conducting research involving primary sources of data such as the survey questionnaire. Along with checking the collected data, reliability analysis also studies the properties of the measurement scales and the items that make them up. Sekaran (2003) states that “the reliability of a measure indicates the extent to which it is without bias (error free) and hence ensures consistent measurement across time and across the various items in the instrument.” In other words, reliability refers to the likelihood of producing the same results if the research is replicated by another researcher following the same procedures. The analysis procedures for reliability calculate a number of commonly used measures of scale reliability and also provide information about the relationships between individual items in the scale. Items that might create problems can be identified and excluded. In this study, Cronbach’s Alpha was used for the reliability test as it is accepted as a highly relevant test to analyse questionnaires based on five-point a Likert scale and it measures the internal consistency of the questionnaire based on the average inter-item correlation of the items. Table 5.2 below provides the results of the reliability analysis of the items that were included in the questionnaire. Sekaran (2003) argues that values less than 0.60 can be considered as showing poor reliability while those in the range of 0.70 are acceptable. As can be seen, Cronbach’s Alpha Coefficient for the measures in this survey is 0.783, so it can be assumed that there is internal reliability of the measures used in the current study.
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Figure 5.2 Results of reliability analysisCronbach’s Alpha Number of items
0.783 28
In general, there are many statistical techniques and methods for analysing quantitative data. For the purposes of achieving the objectives and answering the questions of the current study, several techniques were adopted. The researcher used the SPSS (Software Package for Social Science) to analyse the survey data. The next chapter will explain and report the results of the statistical analysis conducted on the data collected through the survey, but this section will briefly touch upon the methods of statistical tests in the overall research methodology.
Descriptive Statistics Sekaran (2003) argues that descriptive statistic initiates the transformation of raw data into a form that will provide information to describe a set of factors in a situation. The effective use of descriptive statistics helps to express the analysis results as percentages and to present the frequency distribution in percentage form (Pallant 2010). Therefore, descriptive statistics such as frequencies, percentages, means and standard deviation were used in this study. Frequencies and percentages are used to describe the study sample and to assist in answering the research questions relating to the hypotheses for all the variables of company and audit firm characteristics.
Statistical Tests Thietart (2001) argues that, “conclusions or generalisations often have to be established on the basis of observations or results, and in some cases statistics can add to their precision.” So, along with the descriptive statistics, statistical analysis has been used to help to generalise the study findings to the wider population from which the sample was drawn. Chi-square analysis for the sample was conducted to test the significant difference in respondents’ choice of answers on a given variable. In other words, it has been used to determine whether any one choice of answer is favoured significantly more than another for the whole sample. Further, a Chi-square test also was employed to investigate if there are any statistically significant differences in the mean scores of the two sample groups of EA and IFA in relation to their perceptions about each statement regarding audit delay in Libya. Moreover, one sample t-test was used to determine whether the mean of the sample perceptions regarding a number of statements is the same as the hypothesised mean, in this case equal to 3 (as the study employed a 5-point Likert scale, 3 is the middle point). If the mean value is significantly greater than 3, this indicates that respondents have a significantly
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higher consensus on that particular statement, and vice versa. In assessing the relationship between factors (company size, industry type, etc.) and audit delay, a binomial test will be employed to classify the responses into two groups: “there is effect versus no effect” and “strong effect versus weak effect”. If the binomial test shows that the proportion of respondents voting for “there is effect” is significantly (p < 0.05) greater than proportion chosen “there is no effect”, then it can be concluded that the particular factor exerts an influence on audit delay, and vice versa.5.9 Summary
This chapter has outlined the research methodology adopted in this study. It has justified the positivistic research paradigm with quantitative methodology being chosen as the most suitable approach for the conduct of this study as it seeks to generate quanitifiable data about the determinants of audit delay in Libya. Furthermore, it was decided that a survey questionnaire would be used as the main method for collecting data. Every effort was made to ensure that the questionnaire used in the survey was well-designed with questions touching on all the important issues and categorised on a 5-point scale. In designing the questionnaire, several other issues, including the language and wording, question order and accuracy of translated versions, were examined and tested through a pilot study with selected respondents in the field. The data collected from the surveys were coded and processed through the computer and analysed using the SPSS. The methods of descriptive statistics or the statistical analysis used for data analysis were briefly explained in this chapter. The next chapter presents the findings of the statistical analyses of the data collected from the questionnaire surveys.