How to Investigate the Use of Medicines by Consumers
(2004; 98 pages) Ver el documento en el formato PDF
Índice de contenido
Ver el documentoAcknowledgements
Ver el documentoPreface
Abrir esta carpeta y ver su contenido1. Why study medicines use by consumers
Abrir esta carpeta y ver su contenido2. What influences medicines use by consumers
Abrir esta carpeta y ver su contenido3. How to study medicines use in communities
Abrir esta carpeta y ver su contenido4. Prioritizing and analysing community medicines use problems
Abrir esta carpeta y ver su contenido5. Sampling
Cerrar esta carpeta6. Data analysis
Ver el documento6.1 Introduction
Ver el documento6.2 Sorting and ordering data
Ver el documento6.3 Making quality control checks
Ver el documento6.4 Processing qualitative data
Ver el documento6.5 Analysing qualitative data
Ver el documento6.6 Processing quantitative data
Ver el documento6.7 Analysing quantitative data
Ver el documento6.8 Conclusion
Abrir esta carpeta y ver su contenido7. Monitoring and evaluating rational medicines use interventions in the community
Ver el documentoBack cover

6.6 Processing quantitative data

Quantitative data collected with questionnaires or other methods containing a structured set of open and closed questions or observations are easier to process. Prior to processing the data, variables which are being measured have to be listed.

For numerical variables, decisions concerning how to categorize numerical data can be made after they have been collected. For example, for the variable ‘age’ in the inventory of personal medicines, you may decide to have two age groups: 40 and above, and age below 40, with an equal number of respondents in each category. You may also want to have three categories: 20-29, 30-39, and 40 upwards.

For categorical variables, the categories have sometimes been decided on before hand, especially for closed questions. The responses to open-ended questions can be categorized in two steps:

First, list the responses for each question; read through the whole list of answers. Then start giving codes for the answers that you think belong together.

Second, try to find a label for each category. After some shuffling you usually end up with 4 to 6 categories. Note again that you may include a category ‘others’, but that it should be as small as possible, preferably containing fewer than 5% of the total answers.

Coding is important for quantitative studies. If data are entered into a computer for subsequent processing and analysis, it is essential to develop a coding system. For computer analysis, each category of a variable is usually given a number, for example, the answer ‘yes’ may be coded as 1, ‘no’ as 2 and ‘no response’ as 9. The codes should be entered on the questionnaires (or checklists) themselves. When finalizing your questionnaire you should insert a box for the code in the right margin of the page for each question. These boxes should not be used by the interviewer. They are only filled in afterwards during data processing. Take care that you have as many boxes as the number of digits in each code.

For example:

Yes (or positive response)

code - 1

No (or negative response)

code - 2

Don’t know

code - 9

Common responses should have the same code in each question, as this minimizes mistakes by coders.

Note: If you intend to process your data by computer, always consult a person experienced in computer processing before you finalize your questionnaire.

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