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Preparation of qualitative data for statistical analysis and their comparing with self-anchoring questions

Preparation of qualitative data for statistical analysis and their comparing with self-anchoring questions. Author : Assoc . Prof. , PhD . Sigitas V AITKEVI ČIUS.

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Preparation of qualitative data for statistical analysis and their comparing with self-anchoring questions

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  1. Preparation of qualitative data for statistical analysis and their comparing with self-anchoring questions Author: Assoc. Prof. , PhD.Sigitas VAITKEVIČIUS Kaunas University of Technology, Economics and Management Faculty, Management Department (Lithuania) e-mail: sigitas.vaitkevicius@ktu.lt (lang. : lt., en., ru.)

  2. Problem, Methodological context • Up to now are a lot of done in a field of social research . • Created big variety of qualitative and quantitative methods helps researcher to explore and properly to describe explored phenomena. • Nonetheless, because of difference of their nature it's difficult to compare their results. That’s why usually up to now their concepts were separated stating that qualitative methods are designated for identification of phenomena and description of its characteristics. At the same time quantitative methods were used to describe the outspread of phenomena and shifts in its characteristics in the whole population. • Use of these methods usually was applied in this sequence: • This raised the need to create the methodology which will allow to shorten the research time and will be designed for the statistical comparative analysis of qualitative and quantitative data. Moreover, methodology had to meet the methodological goodness criteria such as: objectivity, representativeness, reliability, validity, efficiency and utility.

  3. Problem, Methodological context: Ontological background • If we will start talking about psycho-social reality we will find that itis complicated, multidimensional, contextual, stochastic, and constructive. • It’s mean that if we will start to do the full length research it can take years from identification of phenomena up to description of it in the whole population. Moreover, in some situations extension in time means that we will identify the phenomena in working with one population and we will finish the research working with another. It will not be treated as anti quality if the research object is random and insensitive to the time, but if it is, than we will not be able to compare the results. • Insensitiveness to the time means that if you work with 20 year old persons year by year you will get the same results randomly selecting the persons from the such population. But can be and so that after several years, the earlier described phenomena will not exist in the new 20 year old persons population. More over, because of changes you will not find this phenomena researching the same population which is now for example 22 years old. • One more situation which is needed for such methodology was the need to compare the creative processes with routine processes. There is the need to mention, that we can simply describe the routine process and research it operating by the small number of variables, which are extracted from the complex reality, but if we will start to do the same with the creative process, as for example studying the topic “how people makes decision,” the research that is operating by the small number of variables extracted from the complex reality, could not provide about such reality almost anything eloquent. • MoreoverRepresentatives of qualitative paradigm are criticizing extortionof several abstract variables from the complex reality and partly this is done deservedly.

  4. Problem, Methodological context: Methodological background • Talking about the questionnaires there is a need to mention that mathematically the longer the test, the higher the reliability. Validity and reliability are mathematically interrelated also. • Big and large structure of primary indicators means that construct is fully reflected, consequently valid, but it’s more difficult to fill it. High number of primary items leads towards to long survey instrument. • Long questionnaire as a trait of quality easy could become as a trait of anti-quality. It’s mean that long questionnaires is problematical in filling and they rises such typical problems as: tiredness of respondents which leads to de-motivation and formal filling. • Moreover, sometimes information or some decisions are unimportant to the people until they is not mentioned for them and just then they become very important to them. • So, on a whole – AS a RESULT research becomes unreliable and non valid.

  5. Problem, Methodological context: Methodological background • Research praxis shows, that seeking informativeness questionnaires and earlier were created in combination of open and self-anchoring questions. In this way, upraised the possibility to shorten the questionnaires and get the important, up to this time undisclosed, information about phenomena. • There was the need for methodology which will allow in a quantitative level to contemporize open-ended, close-ended or self-anchoring questions. • That it is possible, emerged from the survey research of notions and attitudes. In some research next to self-anchoring questions we placed and open-ended question, which enabled respondents to enter into the questionnaire their own statements. • During the visual comparative analysis of above mentioned open-ended and self-anchoring questions were noticed, that respondents tend to enter statements which already were evaluated by them using the self-anchoring questions.

  6. Problem, Methodological context: Methodological background MAIN THESIS • It is possible to create methodology which allows statistically compare the answers got by the open-ended and self-anchoring questions. • Moreover, it is possible to make horizontal and vertical comparative analysis of them.

  7. Experience of data analysis : Empiricalandexperiencebasis • Methodological advices about analysis of open-ended and self-anchoring questions are based on experienceof empirical studies. The most important of them are the following: • research on quality of life and satisfaction by municipality provided services ordered by the Lithuanian municipalities; • evaluation of staff capabilities and competencies ordered by the Lithuanian companies; • school children and educators researchordered by the Lithuanian Ministry of Education and Science • dissertational projects: Modelling of strategic analysis instrumentarium in SME’s; The development of managers’ personal qualities and professional skills, Measuring the Effectiveness of Public Relations Programs etc. • It have to be noted, that experience about analysis of self-anchoring and open-ended questions is collected by working in a very diverse populations (in common resident’s population and in such target populations as: managers, school children, students, and staff of very diverse work organizations). • The samples of conducted studies are conditionally high – from 200 till 2000 and more respondents.

  8. Description of method: text analysis • Systematization of text • Content systematization technique created because was the need for the text coding technique. It allow to extract meaning of the text. • This technique consist of forth steps: • Reading of the text and understanding of its overall meaning (based on romanticist, phenomenological, dialectical, critical, or post-structural hermeneutics) • Identification of text's logical structure (construct). (based on Wilkinson (1991) Key and Hook technique) • Dividing the text to the logical passages • Comparative analysis of logical passages and conflation of them to coherent logical sequence

  9. Description of method: text analysis • Coding of categories can be done by text operationalization : • Interpretation of theoretical (Extensive) concept T1 used by respondent in the study; • Classification of T1 to constrictive concepts t1, t2, ..., tnaccording to the content given by the respondents and which have a lower degree of abstraction nor the T1; • description of t1, t2, ..., tn empirical indicators E1, E2, ..., En ; (Expressed by notions or by logical construct) • description of measure scale and confirmation of E1, E2, ..., En metrological criteria e1, e2, ..., en.

  10. Description of method: text analysis • Coding strategies: • Based on confirmed metrological criteria’s there are at least two numerical expression strategies of primary indicators: • use for coding an amount of mentioned notions which belongs to the same theoretical construct t1

  11. Description of method: text analysis • Coding strategies: • Based on confirmed metrological criteria’s there are at least two numerical expression strategies of primary indicators: • dichotomous coding of mentioned notion as 1 and not mentioned as 0 THE SAME TWO CODING STRATEGIES and averaging of notions CAN BE USED FOR NUMERICAL EXPRESSION OF CONCEPTS

  12. Examples of tools design used for vertical comparative analysis of answers to open-ended and self-anchoring questions Dissertation: Modelling of strategic analysis instrumentarium in SME’s • Did you ever heard about organizations’ Mission? If yes, then shortly and simply describe it? • It’s the first time when I hear about it • I heard about it but I am not so good to discuss this • Yes, I had heard about it, Mission is: ______________________________________ • _____________________________________________________________________ Do you have an experience to formulate the company's mission?If yes shortly describe an experience: _____________________________________________________________________________

  13. Examples of tools design used for horizontal comparative analysis of answers to open-ended and self-anchoring questions The development of managers’ personal qualities and professional skills Used in dissertation written by Erika Župerkienė

  14. Examples of tools design used for horizontal comparative analysis of answers to open-ended and self-anchoring questions Measuring the Effectiveness of Public Relations Programs Used in dissertation written by Lina Kazokienė

  15. Statistical analysis of coded data and their comparison with a data got by self-anchoring questions • For statistical analysis of open-ended answers can be used such methods as Factor, Reliability and Cluster analyses as well as for a self-anchoring questions. • Answers got using self-anchoring scale has to be recoded before comparative statistical analysis with open-ended answers • For comparative analysis of coded variables with self-anchoring category rating scales can be used nonparametric tests, crosstabs etc.

  16. Conclusion • This methodology successfully proved and certified in real research practise. It can be used for exploration of new facts and for compare them with known. • Plans for the future: to explore more available advantages and disadvantages of suggested methodology and to make it as a tool for a less experienced researcher.

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