Module 01

Data management I: questionnaire, codebook, data entry, & data import to jamovi

Introduction

  • Many studies involve measuring psychological constructs (e.g., happiness, personality) using questionnaire.

  • After collecting responses from participants on a questionnaire, we need to turn these responses into data and use a systematic method to manage the data.

  • This module introduces some techniques and practice for systematically managing the data obtained from a study using questionnaire.

  • Throughout the course, we will be using jamovi, a free and open software package for statistical analyses, which will be introduced in this module.

Download jamovi

1. Develop a questionnaire

1.1 What is a questionnaire?

    • A questionnaire is a research tool consisting of a set of questions which are designed to gather information about a particular/ multiple theme(s).

1.2. Basic structure of a questionnaire

    • Consent form

      • Consent form is a document to be signed before participating the study by the participant. The participant has the right to understand the detail, benefits, drawbacks and use of data in the study.

    • Demographic data

      • Demographic data refers to the personal information of a participant, e.g., gender, age, and year of study.

    • Scale

      • An instrument for measuring a psychological construct, e.g., a "happiness scale" for measuring happiness.

      • The score on a scale is often computed based on the scores obtained from multiple items.

    • Item

      • An item is often presented as a question or a statement on the questionnaire. In response to each item, the participant gives an answer, usually as a number.

      • For example, a "happiness scale" may contain an item "I smile a lot". The participant will rate how much he/she agrees to this statement, on a scale of, e.g., 1-5.

      • Items presented in a questionnaire for scientific research are often extracted from validated measurement scales. Scale validation is a rigorous scientific process that ensures a scale's validity (more in later lectures).

      • Sometimes, scales that are constructed by the researchers (that have not been validated) may also be included.

1.3. Sample questionnaire


Stat_questionnaire_template.docx

2. Develop a codebook

2.1. What is a codebook?

    • A codebook is a document to store relevant information of the questionnaire.

2.2. Basic field names of a codebook

    • Variable names

      • Variable names are data items collected in the questionnaire. For example, date, gender, and questions.

    • Format

      • Format can also be called level of measurement. For example, nominal, ordinal, and continuous.

    • Description

      • Description is to describe what the variable refers to.

    • Reverse code

      • A scale may contain certain items that are written in an opposite way. These items are called reverse-coded items.

      • E.g., a "happiness scale" may contain an item "I often feel sad.". Reverse coding is a survey technique for checking participants' responses on a multi-item scale.

      • A high score in response to reverse-coded item represents that the person has a low score in terms of the meaning of the actual scale.

      • E.g., a person strongly agrees to the item "I often feel sad" should have a low score in the "happiness scale".

    • Subscale

      • Subscale refers to a subdivision scale under a large scale. A subscale usually represents a particular dimension of a scale that measures a psychological construct.

      • For example, Big five personality scale has 5 subscales including Openness to experience, Agreeableness, Conscientiousness, Extroversion, and Neuroticism.

    • Item

      • Item refers to the actual item presented in the questionnaire. For example, "How old are you?" is presented in the questionnaire.

    • Point

      • Point refers to the number of point scale of a question. For example, a question has a 5-point Likert scale indicating there are 5 points for the participant to rate.

2.3. Demonstration

    • Create a new spreadsheet with any software like Microsoft Excel and Google Spreadsheet.

    • (Here we use Microsoft Excel.)

    • Remember to save the file for future use.

Example 1.1_Develop codebook.mp4

3. Data entry

3.1 Why and how?

    • We want to maintain a record of all raw responses from all participants in a computer file. This is typically done on a spreadsheet software (e.g., MS Excel, Google Sheets).

    • Typically, on the record sheet, one column represents one item in the questionnaire; one row represents one participant.

    • Therefore, a cell in the record sheet represents a particular participant's response to one particular item.

    • At this stage, we enter the raw responses as they are shown in the questionnaire (even for reverse-coded items).

    • We will learn some data processing techniques in later modules.

3.2. Demonstration

    • Open the codebook spreadsheet (the file in 2.3).

    • Create a new spreadsheet with any software like Microsoft Excel and Google Spreadsheet.

    • (Here we use Microsoft Excel.)

    • Note: Comma-Separated Values (CSV) is a file format using a comma to separate values. One of the advantages is easy to read by many software like notepad.

    • ***Remember to save the file as .CSV for future use, so that it can be opened in different applications (e.g., MS Excel, Google Sheets, jamovi, or even notepad)***

Example 1.2_DevelopDatasheet.mp4

4. Import the data to jamovi

4.1. Demonstration

    • Open jamovi.

    • Note: .OMV is a file format specifically used by jamovi. It stores extra information (e.g., scale of measurement, that only jamovi can read.)

    • ***Remember to save the file as .OMV for future use specifically in jamovi.***

Example 1.3_OpenCSVtojamovi.mp4

Module Exercise

Complete the exercise!

    • Now, if you think you're ready for the exercise, you can check your email for the link.

    • Remember to submit your answers before the deadline in order to earn the credits!