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Bayesian data analysis in the phonetic sciences: A tutorial introduction ...
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| 3 |
Recognition of the Mental Workloads of Pilots in the Cockpit Using EEG Signals
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2298 (2022)
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Connecting Text Classification with Image Classification: A New Preprocessing Method for Implicit Sentiment Text Classification
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In: Sensors; Volume 22; Issue 5; Pages: 1899 (2022)
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eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 8; Pages: 4615 (2022)
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Knowledge Discovery from Large Amounts of Social Media Data
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In: Applied Sciences; Volume 12; Issue 3; Pages: 1209 (2022)
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Data-Driven Analysis of European Portuguese Nasal Vowel Dynamics in Bilabial Contexts
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4601 (2022)
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A Novel Method of Generating Geospatial Intelligence from Social Media Posts of Political Leaders
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In: Information; Volume 13; Issue 3; Pages: 120 (2022)
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Illusion of Truth: Analysing and Classifying COVID-19 Fake News in Brazilian Portuguese Language
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In: Big Data and Cognitive Computing; Volume 6; Issue 2; Pages: 36 (2022)
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Extending and Using a Sentiment Lexicon for Latin in a Linked Data Framework ...
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Extending and Using a Sentiment Lexicon for Latin in a Linked Data Framework ...
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Translate Wisely! An Evaluation of Close and Adaptive Translation Procedures in an Experiment Involving Questionnaire Translation
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In: International journal of sociology ; 51 ; 2 ; 135-162 (2022)
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What Constitutes a Local Public Sphere? Building a Monitoring Framework for Comparative Analysis
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In: Media and Communication ; 9 ; 3 ; 85-96 ; Spaces, Places, and Geographies of Public Spheres (2022)
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| 15 |
Generating Samples of Diasporic Minority Populations: A Chilean Example
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In: Targeting International Audiences: Current and Future Approaches to International Broadcasting Research ; 3 ; CIBAR Proceedings ; 138-149 ; Conference of International Broadcasters' Audience Research Services (CIBAR) ; XX (2022)
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| 16 |
The Optimism-Pessimism Short Scale-2 (SOP2): a comprehensive validation of the English-language adaptation
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In: Measurement Instruments for the Social Sciences ; 4 ; 1-14 (2022)
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Multicultural classroom discourse dataset on teachers' and students' dialogic empathy.
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| 18 |
El 14F a Instagram : una proposta d'articulació de tècniques de raspat web i anàlisi de xarxes
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| 19 |
Exploring Optimal Response Labels for Constructing an Interval Type 5-Point Likert Scale
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In: Boise State University Theses and Dissertations (2021)
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Abstract:
Performance improvement practitioners value evidence-based practices, which include data-driven decisions. Data can be obtained through survey questionnaires designed with closed-ended questions and response scales. The Likert scale (Strongly Disagree, Disagree, Neutral, Agree, and Strongly Agree) is one of the most commonly used response scales. Whether the 5-point Likert scale, as a verbal descriptor scale, should be treated as an ordinal or interval scale is an on-going debate, as different types of statistical analyses are applied to ordinal and interval data. I conducted this study to examine if survey participants would perceive a 5-point Likert scale close to an interval level measurement when an adverb such as Moderately, Somewhat, or Slightly is added in front of Agree and Disagree. This information could be used by researchers who wish to construct an interval type Likert scale. I conducted this study using a convenient sample of performance improvement practitioners, including master’s degree and graduate certificate seeking students, recent alumni, and faculty in the Organizational Performance and Workplace Learning department at Boise State University. For this study, I developed a web-based survey instrument using a horizontal slider format. The first screen of the survey instrument contained eight partially-labeled Likert scale sliders, each of which presented three anchors in ascending order (Strongly Disagree on the far-left side, Neutral in the middle, and Strongly Agree on the far-right side) along with their numerical values (-2, 0, and +2, respectively). The slider bar was initially placed on Neutral (0). Participants were instructed to move the slider bar to locate each of the following eight anchors on the Likert scale slider; Disagree, Moderately Disagree, Somewhat Disagree, Slightly Disagree, Agree, Moderately Agree, Somewhat Agree, and Slightly Agree. To test the response order effect, the second screen of the instrument asked the participants to repeat the above procedure using another set of eight Likert scale sliders presented in descending order. The third screen of the instrument asked for participants’ gender, age group, and native English speaker status. The data was collected in October of 2020. The web-based survey system (Qualtrics) recorded data rounding to two decimal points and provided summary report data including mean, standard deviation, variance, and minimums and maximum response scores for each item. A survey invitation was sent to 327 practitioners, and a total of 109 of them submitted the survey. However, the initial data screening detected 37 datasets with responses where any responses were incomplete or used the incorrect side of the slider continuum, which were excluded. Two additional responses from non-native English speakers were also excluded due to the linguistic aspect of the study. This left 70 responses available for analysis (51 females, 18 males, 1 “do not want to report”). The anchor being tested would be considered useful for constructing an interval measurement if its corresponding confidence interval included the value -1 or +1. To test this, 95% confidence intervals were constructed for each of the 16 items. Response order effects were investigated by performing paired sample t-tests comparing the average scores of the 8 response options when presented in ascending versus descending order. The results showed that, Moderately Disagree and Moderately Agree were closely aligned with -1 or +1 on the continuum, respectively, regardless of the response orders used. Agree was aligned with +1 only when presented in ascending order, but not when presented in descending order. Adding other adverbs Somewhat and Slightly to Agree and Disagree made the 5-point Likert scales to be clearly ordinal scales in both response orders used. Therefore, the study concluded that when one needs to collect interval data from a 5-point Likert scale, Moderately Agree and Moderately Disagree can be used in either ascending or descending order of the scale. Although Somewhat would not be a good adverb to be added to Disagree and Agree when the 5-point Likert scale is expected to generate interval data, an unexpected interesting finding was that Strongly Agree, Somewhat Agree, Somewhat Disagree, and Strongly Disagree in descending order can be used as an interval-level 4-point Likert scale. This study was conducted with several limitations including the use of a convenience sample, and the generalization of the findings may be limited.
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Keyword:
and Operations; Business Administration; data analysis; interval; level of measurement; Likert; Management; response scale; survey design
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URL: https://scholarworks.boisestate.edu/td/1778
https://scholarworks.boisestate.edu/cgi/viewcontent.cgi?article=2913&context=td
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| 20 |
Writing At the Horizon: How Producing Imagined Narratives Affects Mood
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In: Senior Projects Fall 2021 (2021)
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