Therefore, the number of observation varies for each question. In total, the questionnaire used in the survey included 14 questions. Our discussion of theoretical backgrounds and development in the further analysis of the survey variables can be found in the associated research article  Table 3. The questionnaire consists of three parts. The first part includes basic information of respondents. The second part has several questions regarding the use of social media use.
Our research design is mainly based on the theoretical framework . Social and mass media could influence the risk perception  because the information might refer to heuristics. Thus, our questionnaire includes social media use behavior, which might contribute to the perceived risk in each sample. The personal characteristics are the potential sources that have an impact on risk perception . These studies are our referred sources to design the questionnaire regarding the COVID risk perception.
In addition, apart from risk perception, the respondents were asked to consider the level of fake news as well as the overwhelming news of governmental office about COVID in the point Likert scale. Therefore, we asked the participant the level of overwhelming information on the online platform that they used to search for COVID information.
Survey data were collected through an anonymous self-administered questionnaire on the Internet platform. We randomly distributed the questionnaires to three regions in Vietnam North, Central and South. The analysis of our data could be done by STATA and other software to visualize and use for further econometric models.
Therefore, follow-up studies might extend our work and enable to determine some helpful features to succeed in the containment of COVID The author declares that there are no known competing financial interests or personal relationships that have or could be perceived to have influenced the work reported in this article. I am grateful to the anonymous reviewer and managing editor for their helpful comments.
I would like to dedicate this work to my country, Vietnam, for everything that we did together to fight against COVID I owe my country for the whole life. I thank the doctors, nurses, and military soliders for everything that they provided the best condition for me. The usual disclaimers apply. Supplementary material associated with this article can be found, in the online version, at doi: Data Brief.
Published online Apr Toan Luu Duc Huynh. Author information Article notes Copyright and License information Disclaimer. Toan Luu Duc Huynh: nv. This article has been cited by other articles in PMC. Associated Data Supplementary Materials mmc1. Type of data Table How data were acquired Survey Data format Data are in raw format and have been analyzed.
An Excel file with data has been uploaded. Parameters for data collection There is no parameter used for data collection. It is randomized. Description of data collection Data were collected from a random sample of an Internet research source, which provided an electronic questionnaire. Data have been collected since February 1, , when the Vietnamese Prime minister officially declared the global and national emergency scenario.
Economics Bulletin , 40 1 , Open in a separate window. Value of the data 1. Our data are important because this is the first data collection at the primary level to understand the risk perception in the world regarding the COVID pandemic.
Researchers, educators, policymakers, and all institutions involved in public health can benefit from our data because by using these data, they can understand the risk perception in Vietnam for the COVID epidemic. These data can be reused for further insights and development of experiments by comparing the cross-country findings or contributing to meta-analysis in the future. These data can be applied in short term and long term because the COVID pandemic is a global emergency.
Thus, it is timely data collection, which is considered as the additional value of our data. Table 1 Data summary of continuous variables. The table as a whole is the Likert scale. Historic Trivia: The Likert scale question itself was invented by the educator and psychologist Rensis Likert in his thesis at Columbia University.
You never know when this might come up in Market Research Trivia night at your local bar. In our example above, the scale would be 4 to The actual scale labels, as well as the numeric scale itself, may vary. Our example is a nearly perfect Likert scale. The traditional way to report on a Likert scale is to sum the values of each selected option and create a score for each respondent.
This score is then used to represent a specific trait — satisfied or dissatisfied, for example — particularly when used for sociological or psychological research. In these cases the scores can be used to create a chart of the distribution of opinion across the population.
Important tip: for the score to have meaning, each item in the scale should be closely related to the same topic. In a customer satisfaction survey , for example, you should ask all your questions about the product together, all the questions about checkout together, and so on. Ideally in a Likert scale question all of the items will be categorically similar so that the summed score becomes a reliable measurement of the particular behavior or psychological trait you are measuring.
That trait might be overall happiness, or the likelihood to vote for a particular political party, but in either case you must pick a topic and stick with it to get accurate data. This is a very useful question type when you want to get an overall measurement of sentiment around a particular topic, opinion, or experience and to also collect specific data on factors that contribute to that sentiment. You should not use this form of question or at least not call it a Likert scale when the items in the question are unrelated to each other, or when the options are not presented in the form of a scale.
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Business will have to constantly look for transformations in their processes, Product lines, Customer services and brand image to thrive in the system. Data plays an important role in its transformation journey to achieve the end goal. Business cannot sail in this exercise with subjective and hearsay information. They will have to collect objective information on their current products, services, environment and competition from all its stakeholders to start the journey.
Surveys, Questionnaire and interviews are some of the channels through which feedback from all stakeholders are elicited. The response in the feedback may be quantitative data or non-quantitative. Both these types of data will have to be analyzed to gain useful insights. The insights will be used to drive business transformation. Similar Surveys and Questionnaires are deployed as psychometric tests in measuring the skill, knowledge, traits and capabilities of the people in the Job selection, promotion and special assignments.
Likert scale is the way of measuring and analyzing the responses in the surveys and tests. In this article let us study the features of Likert scale. Each Likert item is a simple statement and the participant has to evaluate the statement and fill up response against the subjective or objective options which expresses his level of agreement of disagreement for the Likert item.
The objective of the question may be to elicit responses under various categories. The possible responses under various categories are listed below. Likert scaling mostly is bi-polar and it has negative, positive and neutral values. Tags: None. Weiwen Ng. Pragya, the question is too vague to answer easily.
You said a 5-point Likert scale - do you mean you have one question that's a 5-point Likert item, or do you mean you have several 5-point Likert items that form a scale? If you are using a validated scale, you might consider just proceeding with a regression analysis. If you have one 5-point Likert item, you would be best advised to use ordinal logistic or probit regression little to no substantive difference between the two.
If you have a scale, most people would sum the items up and use a linear regression. That's the simplest approach. There is valid criticism of this approach, however. If you are not using a validated scale, then you may wish to think about doing some basic checks. You could run Cronbach's Alpha help alpha , but this statistic is also not without flaws.
You could run an exploratory factor analysis help factor to check if your scale is consistent with a one-factor solution. There are more complex ways to go about showing construct validity. Please use the command -dataex- to show a representative sample of data; it is installed already if you have Stata Comment Post Cancel.
I have almost 10 questions on 5 pt. Then when I use the tab command i get range of 9 to Now how to proceed further?? I read that you need to deduct 5 or 10 to get better scores.. Maarten Buis. Subtracting a constant is a linear transformation, so that does not change anything substantive. So that is not a priority. It is still unclear what you want to do with the index you created.
You are asking us what your next step should be, but that obviously depends on the direction you want to go. Sir, Im unable to understand as to how to use these scores obtained after summation for analysis waterstress Freq.