Analysis of data which has been collected by questioning

Analysis of data from questionnaires and interviews can serve several purposes. Firstly, analysis of responses from individuals and from groups can provide valuable information about their

prejudices and biases. Secondly, analysis of responses to specific questions can be used to determine their relative difficulty, as in techniques of attitude scaling or item analysis. Principally, analysis is used to summarise and manipulate the data. This third purpose poses difficult

problems because a great deal of the data from questioning is likely to be categorical and qualitative.

Quantitative analysis: Questionnaires are usually designed so that data are collected in a way that will make them amenable to quick tabulation, quantification and quantitative analysis.

The concept of levels of measurement and the admissible

mathematical operations at different levels was discussed with regard to methods of scaling. The same principles apply to data collected on questionnaires.

The simplest statistical analyses involve straightforward frequency counts of responses. Tests of association compare the proportions in each response category or group. They allow calculations to be made of the probability that a difference as great or greater than that obtained could have arisen by chance;

and, therefore, whether or not it is significant. The choice of statistical tests is critical for data forming ranking or

rating scales which are collected in response to fixed alternative questions (Huff, 1973). Any statistical test which involves

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-calculation of the mean (x)assumes data at the level of

interval or ratio scales. In general, the simpler assumptions required by non-parametric tests (Siegel, 1956; Daniel, 1978) make them more appropriate to data from questionnaires. These data are usually in the form of proportions or percentages or, at best, they may be ordinally scaled.

Quantitative analysis of interview data is concerned with the semantic content of the material: the frequency of occurrence of words, assertions, symbols and themes in transcriptions and written records. This concern implies that frequency is the valid index of concern, intensity and the like. However, although

statistical procedures may be used to indicate the likelihood of generalisations from the sample data being valid or not, enumeration carries with it a bias in the selection of problems to be investigated (Holsti, 1969). This makes the procedure appropriate to analysis of data from questionnaires which have been pre-coded by the choice of responses offered. It is less appropriate to analysis of data from interviews, where emphasis is in the direction of the significance of a problem or assertion rather than the assertion itself. The use of quantitative methods in these circumstances poses problems such a s :

Should the number of interviews in which each assertion is made be tabulated?

Or should the number of times an assertion is made in each interview be tabulated?

Or should both be tabulated?

The frequency of occurrence of an assertion may not necessarily be related to its importance because the non-appearance of an assertion may be highly significant also. In this respect, and

particularly if respondents are well-educated and have an extensive vocabulary, it might be more valuable to tabulate the terms which are used in reference to particular assertions rather than the frequency of the assertions themselves•

Qualitative analysis: This method of analysis (Schutz, 1958;

Webb et al, 1966) suggests that researchers participate in the construction of the data they gather by probing their own fundamental assumptions instead of setting them up as boundaries to the investigation.

Instead of using a preconceived scheme for coding data, the researcher reads the record of each interview or the transcript to get "a feel for" the data. He allows critical categories for analysis to emerge from them. Such a process requires pro­

tection against idiosyncratic interpretation or misinterpretation of data because of the potential for exercise of bias by the researcher. Analysis might easily go beyond the manifest

issues communicated by respondents to more latent aspects, and the researcher may infer what was implied or meant in order to create categories (Holsti, 1969).

Choice of methods of analysis: A methodological controversy exists between quantitative methods and qualitative methods.

The former methods are more controlled and they offer greater reproducibility. Therefore, the data are likely to be thought more reliable and the results to have more extended application.

However, although quantitative analysis has been assisted by increasingly sophisticated techniques, it is not necessarily

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-considered to have been accompanied by a growth of understanding (Phillips, 1976). This may be because, essentially, both

quantitative and qualitative methods depend upon the researcher’s ability to select the most appropriate method, technique or

test, and on the advice he or she receives to assist that choice. Computer programs for quantitative analysis (cf., e.g Nie et al, 1970) are facile, quick and all-too-easy to use. Brigham (1975) has warned that such programs may not offer the optimal analysis for the data concerned, nor may they perform the most appropriate statistical tests.

Conversely, qualitative or descriptive analytic methods are vulnerable to criticism concerning their supposed lack of objectivity. Consequently, inferences or general statements based on them are commonly supposed to be less well-founded than those based on the results of quantitative analysis.

However, Phillips (1976) has written that learning gained by all research methods is a basis for improving scientific method in general because all methods are "merely human construction" and are subject to continuing change.

Lazarsfeld and Barton (1951) and Goode and Hatt (1952) have stressed that concepts of qualitative and quantitative are not dichotomous but constitute a continuum. There is a quantitative element to qualitative analysis, if only because the researcher uses two classes of data ("asserted/not

asserted") in order to determine the significance of assertions.

While quantitative analysis is appropriate to data from questionnaires and qualitative analysis is appropriate to

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-data from interviews, Tukey's point is pertinent .

He emphasised that analysis of data must progress by approximate answers, because knowledge of what is really the problem will, at best, be approximate also.

"Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made more precise."

(Tukey, 1962)

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-SUMMARY

In order to develop a physiotherapeutic assessment which incorporates all of the desirable qualities which have been discussed, several sets of data must be collected, including data from clinicians which can be used to confirm the clinical acceptability of the assessment.

Techniques of the survey approach can overcome the temporal limitations of both the archival approach and the experimental approach to collection of data. Although remebrances of the past and ideas about the future are easily distorted to meet the needs of the present, researchers can learn about on-going

processes from retrospective and prospective questioning using self-administered questionnaires or researcher-administrated interview schedules.

The interview should be used to collect data which cannot be requested on paper. Therefore, questionnaires are considered more appropriate to collection of relatively uncomplicated facts

and opinions: conversely, interviews are more appropriate to collection of data concerning complex individual experiences, relationships or behaviour. The latter data may form a

pattern over many interviews, yielding emergent issues during analysis which are inaccessible to the "vertical sampling" of

questionnaires.

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-CONCLUSIONS

There is a need for a standardised physiotherapeutic assessment of hemiplegia of confirmed reliability and validity for clinical use. Such an assessment would possess the potential to increase effective knowledge of physiotherapy for hemiplegia and

rehabilitation of stroke patients. Specifications for the performance and appearance of the assessment lie in four main are as:

A. Construction of a scale of items of assessment to