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Journal articles on the topic 'Likert'

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Published: 4 June 2021
Last updated: 19 February 2022

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1

Pye, Hayley, Saurabh Singh, Joseph M. Norris, Lina M. Carmona Echeverria, Vasilis Stavrinides, Alistair Grey, Eoin Dinneen, et al. "Evaluation of PSA and PSA Density in a Multiparametric Magnetic Resonance Imaging-Directed Diagnostic Pathway for Suspected Prostate Cancer: The INNOVATE Trial." Cancers 13, no. 8 (April 20, 2021): 1985. http://dx.doi.org/10.3390/cancers13081985.

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Objectives: To assess the clinical outcomes of mpMRI before biopsy and evaluate the space remaining for novel biomarkers. Methods: The INNOVATE study was set up to evaluate the validity of novel fluidic biomarkers in men with suspected prostate cancer who undergo pre-biopsy mpMRI. We report the characteristics of this clinical cohort, the distribution of clinical serum biomarkers, PSA and PSA density (PSAD), and compare the mpMRI Likert scoring system to the Prostate Imaging–Reporting and Data System v2.1 (PI-RADS) in men undergoing biopsy. Results: 340 men underwent mpMRI to evaluate suspected prostate cancer. 193/340 (57%) men had subsequent MRI-targeted prostate biopsy. Clinically significant prostate cancer (csigPCa), i.e., overall Gleason ≥ 3 + 4 of any length OR maximum cancer core length (MCCL) ≥4 mm of any grade including any 3 + 3, was found in 96/195 (49%) of biopsied patients. Median PSA (and PSAD) was 4.7 (0.20), 8.0 (0.17), and 9.7 (0.31) ng/mL (ng/mL/mL) in mpMRI scored Likert 3,4,5 respectively for men with csigPCa on biopsy. The space for novel biomarkers was shown to be within the group of men with mpMRI scored Likert3 (178/340) and 4 (70/350), in whom an additional of 40% (70/178) men with mpMRI-scored Likert3, and 37% (26/70) Likert4 could have been spared biopsy. PSAD is already considered clinically in this cohort to risk stratify patients for biopsy, despite this 67% (55/82) of men with mpMRI-scored Likert3, and 55% (36/65) Likert4, who underwent prostate biopsy had a PSAD below a clinical threshold of 0.15 (or 0.12 for men aged <50 years). Different thresholds of PSA and PSAD were assessed in mpMRI-scored Likert4 to predict csigPCa on biopsy, to achieve false negative levels of ≤5% the proportion of patients whom who test as above the threshold were unsuitably high at 86 and 92% of patients for PSAD and PSA respectively. When PSA was re tested in a sub cohort of men repeated PSAD showed its poor reproducibility with 43% (41/95) of patients being reclassified. After PI-RADS rescoring of the biopsied lesions, 66% (54/82) of the Likert3 lesions received a different PI-RADS score. Conclusions: The addition of simple biochemical and radiological markers (Likert and PSAD) facilitate the streamlining of the mpMRI-diagnostic pathway for suspected prostate cancer but there remains scope for improvement, in the introduction of novel biomarkers for risk assessment in Likert3 and 4 patients, future application of novel biomarkers tested in a Likert cohort would also require re-optimization around Likert3/PI-RADS2, as well as reproducibility testing.
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2

Kim, Kwangmin. "Likert Scale." Korean Journal of Family Medicine 32, no. 1 (2011): 1. http://dx.doi.org/10.4082/kjfm.2011.32.1.1.

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3

Stratton, Samuel J. "Likert Data." Prehospital and Disaster Medicine 33, no. 2 (March 28, 2018): 117–18. http://dx.doi.org/10.1017/s1049023x18000237.

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4

Emerson, Robert Wall. "Likert Scales." Journal of Visual Impairment & Blindness 111, no. 5 (September 2017): 488. http://dx.doi.org/10.1177/0145482x1711100511.

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5

Albaum, Gerald. "The Likert Scale Revisited." Market Research Society. Journal. 39, no. 2 (March 1997): 1–21. http://dx.doi.org/10.1177/147078539703900202.

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This study examined the effect of alternative scale formats on reporting of intensity of attitudes on Likert scales of agreement. A standard one-stage format and an alternate two-stage format were tested in three separate studies on samples of university students in three countries. In general the two-stage format generated the greatest percentage of extreme-position (i.e. most intense) responses across scales. A test of predictive ability showed that the two-stage format was a better predictor of product preferences. Underlying data structures did not differ much between the two.
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6

Duncan, Otis Dudley, and Magnus Stenbeck. "Are Likert scales unidimensional?" Social Science Research 16, no. 3 (September 1987): 245–59. http://dx.doi.org/10.1016/0049-089x(87)90003-2.

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7

Valencia Pomareda, Pedro Herbert. "ESTILOS GERENCIALES Y SATISFACCIÓN LABORAL." Gestión en el Tercer Milenio 17, no. 34 (December 29, 2014): 61–71. http://dx.doi.org/10.15381/gtm.v17i34.11695.

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Desde los experimentos de Howthorne, la administración continuó buscando la mejor manera de superar las relaciones que se tienen con los colaboradores. Es así que siendo el Liderazgo un elemento importante en la gestión estratégica, escogimos entre los muchos estilos de liderazgo el de Rensis Likert, por ser el más técnico y apropiado para logran con mayor efectividad el empowerment, estableciendo el grado de satisfacción que los estilos de Liderazgo de Liker buscan en nuestros colaboradores. Es por ello que buscamos conocer el nivel de satisfacción laboral que los estilos de liderazgo de Likert, logran a través de la teoría de Herzberg.
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8

Shiina, Kenpei. "Cursor movement in Likert ratings." Proceedings of the Annual Convention of the Japanese Psychological Association 82 (September 25, 2018): 3EV—046–3EV—046. http://dx.doi.org/10.4992/pacjpa.82.0_3ev-046.

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9

Joshi, Ankur, Saket Kale, Satish Chandel, and D. Pal. "Likert Scale: Explored and Explained." British Journal of Applied Science & Technology 7, no. 4 (January 10, 2015): 396–403. http://dx.doi.org/10.9734/bjast/2015/14975.

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10

Gritsch, Simone. "Die Likert-Skala – Meinungen abbilden." ergopraxis 5, no. 01 (January 2012): 16–17. http://dx.doi.org/10.1055/s-0031-1300814.

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11

Gunderman, Richard B., and Stephen Chan. "The 13-Point Likert Scale." Academic Radiology 20, no. 11 (November 2013): 1466–67. http://dx.doi.org/10.1016/j.acra.2013.04.010.

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12

Suasapha, Anom Hery. "SKALA LIKERT UNTUK PENELITIAN PARIWISATA; BEBERAPA CATATAN UNTUK MENYUSUNNYA DENGAN BAIK." JURNAL KEPARIWISATAAN 19, no. 1 (March 10, 2020): 26–37. http://dx.doi.org/10.52352/jpar.v19i1.407.

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Artikel ini merupakan sebuah artikel studi literatur (literature review article) yang disusun dengan metode literatur review. Hal yang mendasari penulisan artikel ini adalah keinginan untuk memahami lebih baik mengenai Skala Likert dengan membaca beberapa literatur dan menuangkan hasilnya ke dalam bentuk manuskrip. Topik yang diulas melalui penulisan artikel ini adalah mengenai Skala Likert, sehingga kata kunci yang dipergunakan untuk mengumpulkan data, yang dalam hal ini adalah pustaka berupa buku maupun artikel jurnal adalah “Skala Likert”. Sebanyak 27 pustaka yang membahas mengenai Skala Likert telah dibaca. Mengingat Sebagian besar literatur yang dibaca adalah berupa buku yang terdiri atas banyak topik dan halaman, maka teknik membaca berupa scan, skim dan understand telah diaplikasikan. Ide utama dari penulisan artikel ini adalah untuk memaparkan semaksimal mungkin mengenai Skala Likert berdasarkan karya asli penemunya, untuk kemudian diperkuat dengan berbagai pendapat dari pakar lain mengenai Skala Likert, termasuk penggunaanya di bidang ilmu pariwisata. Bagi penulis, Literatur review mengenai Skala Likert ini menghasilkan pemahaman yang lebih baik mengenai Skala Likert dan apa saja yang harus dipertimbangkan untuk menyusun kuesioner Skala Likert dengan baik. Diharapkan, manfaat yang sama juga dapat dirasakan oleh pembacanya kelak.
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13

Albaum, Gerald, and Brian D. Murphy. "Extreme Response on a Likert Scale." Psychological Reports 63, no. 2 (October 1988): 501–2. http://dx.doi.org/10.2466/pr0.1988.63.2.501.

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This study examined the effect of alternative scale formats on reporting of extreme attitudes on Liken scales of agreement. The formats were tested on samples of university students who responded to a set of statements about economic systems. In general, a two-stage format generated a greater percentage of extreme-position responses than did the common one-stage format, with a modified one-stage version falling in between.
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14

Hartley, James. "Some thoughts on Likert-type scales." International Journal of Clinical and Health Psychology 14, no. 1 (January 2014): 83–86. http://dx.doi.org/10.1016/s1697-2600(14)70040-7.

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15

Gregoire, Timothy G. "Analysis of Likert-scale data revisited." Psychological Bulletin 105, no. 1 (January 1989): 171. http://dx.doi.org/10.1037/h0092469.

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16

Böckenholt, Ulf. "Measuring response styles in Likert items." Psychological Methods 22, no. 1 (2017): 69–83. http://dx.doi.org/10.1037/met0000106.

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17

Watson, Nicholas C. "Likert or Not, We Are Biased." Anesthesiology 116, no. 5 (May 1, 2012): 1160. http://dx.doi.org/10.1097/aln.0b013e3182503a86.

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18

Pell, Godfrey. "Use and misuse of Likert scales." Medical Education 39, no. 9 (September 2005): 970. http://dx.doi.org/10.1111/j.1365-2929.2005.02237.x.

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19

Vickers, Andrew J. "COMPARISON OF AN ORDINAL AND A CONTINUOUS OUTCOME MEASURE OF MUSCLE SORENESS." International Journal of Technology Assessment in Health Care 15, no. 4 (October 1999): 709–16. http://dx.doi.org/10.1017/s0266462399154102.

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The relationship between an ordinal (Likert) and a continuous (visual analog) measure of pain was investigated in 400 long-distance runners experiencing delayed-onset muscle soreness. Subjects completed a 100-mm visual analog scale (VAS) and a 7-point Likert scale twice a day for 5 days, starting at 9:00 PM on the evening of the run. The relationship between scales was modeled by calculating the median VAS for each Likert score and the modal Likert score for each point on the VAS. Standardized means were calculated by dividing the total of 5 day scores by the standard error of 5 day scores for all subjects. The relationship between scales was approximately linear, but VAS scores recorded concurrently with each Likert score varied enormously. VAS responses for a Likert score of zero were lower than expected, apparently because subjects chose zero only if they were completely free of soreness. The standardized mean of the Likert scale was higher (34.1 [SD 20] versus 30.4 [SD20] p <<< .0001), suggesting greater responsiveness. The Likert scale can be recommended as a method of measuring muscle soreness, but researchers should not anchor the lowest score to zero pain.
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20

Zawaideh, Jeries P., Evis Sala, Maria Pantelidou, Nadeem Shaida, Brendan Koo, Iztok Caglic, Anne Y. Warren, et al. "Comparison of Likert and PI-RADS version 2 MRI scoring systems for the detection of clinically significant prostate cancer." British Journal of Radiology 93, no. 1112 (August 2020): 20200298. http://dx.doi.org/10.1259/bjr.20200298.

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Objective: To compare the performance of Likert and Prostate Imaging–Reporting and Data System (PI-RADS) multiparametric (mp) MRI scoring systems for detecting clinically significant prostate cancer (csPCa). Methods: 199 biopsy-naïve males undergoing prostate mpMRI were prospectively scored with Likert and PI-RADS systems by four experienced radiologists. A binary cut-off (threshold score ≥3) was used to analyze histological results by three groups: negative, insignificant disease (Gleason 3 + 3; iPCa), and csPCa (Gleason ≥3 +4). Lesion-level results and prostate zonal location were also compared. Results: 129/199 (64.8%) males underwent biopsy, 96 with Likert or PI-RADS score ≥3, and 21 with negative MRI. A further 12 patients were biopsied during follow-up (mean 507 days). Prostate cancer was diagnosed in 87/199 (43.7%) patients, 65 with (33.6%) csPCa. 30/92 (32.6%) patients with negative MRI were biopsied, with an NPV of 83.3% for cancer and 86.7% for csPCa. Likert and PI-RADS score differences were observed in 92 patients (46.2%), but only for 16 patients (8%) at threshold score ≥3. Likert scoring had higher specificity than PI-RADS (0.77 vs 0.66), higher area under the curve (0.92 vs 0.87, p = 0.002) and higher PPV (0.66 vs 0.58); NPV and sensitivity were the same. Likert had more five score results (58%) compared to PI-RADS (36%), but with similar csCPa detection (81.0 and 80.6% respectively). Likert demonstrated lower proportion of false positive in the predominately AFMS-involving lesions. Conclusion: Likert and PI-RADS systems both demonstrate high cancer detection rates. Likert scoring had a higher AUC with moderately higher specificity and lower positive call rate and could potentially help to reduce the number of unnecessary biopsies performed. Advances in knowledge: This paper illustrates that the Likert scoring system has potential to help urologists reduce the number of prostate biopsies performed.
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Kang, Man-Ki, Chang-Eun Lee, and Gue-Tak Chio. "Fuzzy Hypotheses Testing of Likert Fuzzy Scale." Journal of Korean Institute of Intelligent Systems 15, no. 5 (October 1, 2005): 533–37. http://dx.doi.org/10.5391/jkiis.2005.15.5.533.

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22

Uz Zaman, Nadeem, Zainab Bibi, Sana Ur Rehman Sheikh, and Abdul Raziq. "Manualizing Factor Analysis of Likert Scale Data." Journal of Management Sciences 7, no. 2 (October 2020): 56–67. http://dx.doi.org/10.20547/jms.2014.2007204.

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23

Mirahmadizadeh, Alireza, Hamed Delam, Mozhgan Seif, and Reyhaneh Bahrami. "Designing, Constructing, and Analyzing Likert Scale Data." Journal of Education and Community Health 5, no. 3 (December 1, 2018): 63–72. http://dx.doi.org/10.21859/jech.5.3.63.

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24

Jamieson, Susan. "Likert scales: how to (ab)use them." Medical Education 38, no. 12 (December 2004): 1217–18. http://dx.doi.org/10.1111/j.1365-2929.2004.02012.x.

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25

Chan, Jason C. "Response-Order Effects in Likert-Type Scales." Educational and Psychological Measurement 51, no. 3 (September 1991): 531–40. http://dx.doi.org/10.1177/0013164491513002.

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FLASKERUD, JACQUELYN H. "Is the Likert Scale Format Culturally Biased?" Nursing Research 37, no. 3 (May 1988): 185???186. http://dx.doi.org/10.1097/00006199-198805000-00013.

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27

Carr, Stuart C., Vanessa Powell, Maria Knezovic, Don Munro, and Malcolm MacLachlan. "Measuring motivational gravity: Likert or scenario scaling?" Journal of Managerial Psychology 11, no. 5 (August 1996): 43–47. http://dx.doi.org/10.1108/02683949610124816.

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Flaskerud, Jacquelyn H. "Cultural Bias and Likert-Type Scales Revisited." Issues in Mental Health Nursing 33, no. 2 (January 25, 2012): 130–32. http://dx.doi.org/10.3109/01612840.2011.600510.

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Drasgow, Fritz, Oleksandr S. Chernyshenko, and Stephen Stark. "75 Years After Likert: Thurstone Was Right!" Industrial and Organizational Psychology 3, no. 4 (December 2010): 465–76. http://dx.doi.org/10.1111/j.1754-9434.2010.01273.x.

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For over three-quarters of a century researchers and practitioners have analyzed rating scale data using methods that assume a dominance response process wherein an individual high on the trait assessed is assumed to answer positively with high probability. This approach derives from Likert's famous 1932 approach to the development and analysis of rating scales. In this paper, we argue that Likert scaling and related methods are misguided. Instead, we propose that methods that have evolved from Thurstone (1927, 1928, 1929) scaling provide a better representation of the choice process underlying rating scale judgments. These methods hypothesize an ideal point response process where the probability of endorsement is assumed to be directly related to the proximity of the statement to the individual's standing on the assessed trait. We review some research showing the superiority of ideal point methods for personality assessment and then describe several settings in which ideal point methods should provide tangible improvements over traditional approaches to assessment.
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Woods, Carol M. "Ramsay Curve IRT for Likert-Type Data." Applied Psychological Measurement 31, no. 3 (May 2007): 195–212. http://dx.doi.org/10.1177/0146621606291567.

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31

Hodge, D. R., and D. Gillespie. "Phrase completions: An alternative to Likert scales." Social Work Research 27, no. 1 (March 1, 2003): 45–55. http://dx.doi.org/10.1093/swr/27.1.45.

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Mellor, D., and K. A. Moore. "The Use of Likert Scales With Children." Journal of Pediatric Psychology 39, no. 3 (October 24, 2013): 369–79. http://dx.doi.org/10.1093/jpepsy/jst079.

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33

Gobo, Giampietro. "Ritorno a Likert. Verso una survey discorsiva." SOCIOLOGIA E RICERCA SOCIALE, no. 88 (December 2009): 5–28. http://dx.doi.org/10.3280/sr2009-088001.

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- For decades, the dilemma between open-ended and closed-ended response alternatives occupied the methodological debate. Over the years, dominant approaches in survey have reacted to this dilemma by opting for fixed response alternatives and the standardization of interviewer's behaviour. If this methodological decision has been the survey's fortune, making it the methodology most widely used in the social sciences, however it produces a large amount of biases well known in the literature. In order to re- medy these biases an alternative proposal can be designed by re-discovering and adapting two «old» proposals: Likert's technique called «fixed question/free answers», and Galtung's procedure named «open question/closed answer». Both procedures are guided by the same principle: make the interview into a conversation, let the interviewee answer freely in his/her own words, and thus release him/her from the researcher's schemes.
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Bartlett, Kathleen W., Shari A. Whicker, Jack Bookman, Aditee P. Narayan, Betty B. Staples, Holly Hering, and Kathleen A. McGann. "Milestone-Based Assessments Are Superior to Likert-Type Assessments in Illustrating Trainee Progression." Journal of Graduate Medical Education 7, no. 1 (March 1, 2015): 75–80. http://dx.doi.org/10.4300/jgme-d-14-00389.1.

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Abstract Background The Pediatrics Milestone Project uses behavioral anchors, narrative descriptions of observable behaviors, to describe learner progression through the Accreditation Council for Graduate Medical Education competencies. Starting June 2014, pediatrics programs were required to submit milestone reports for their trainees semiannually. Likert-type scale assessment tools were not designed to inform milestone reporting, creating a challenge for Clinical Competency Committees. Objective To determine if milestone-based assessments better stratify trainees by training level compared to Likert-type assessments. Methods We compared assessment results for 3 subcompetencies after changing from a 5-point Likert scale to milestone-based behavioral anchors in July 2013. Program leadership evaluated the new system by (1) comparing PGY-1 mean scores on Likert-type versus milestone-based assessments; and (2) comparing mean scores on the Likert-type versus milestone-based assessments across PGY levels. Results Mean scores for PGY-1 residents were significantly higher on the prior year's Likert-type assessments than milestone-based assessments for all 3 subcompetencies (P &lt; .01). Stratification by PGY level was not observed with Likert-type assessments (eg, interpersonal and communication skills 1 [ICS1] mean score for PGY-1, 3.99 versus PGY-3, 3.98; P = .98). In contrast, milestone-based assessments demonstrated stratification by PGY level (eg, the ICS1 mean score was 3.06 for PGY-1, 3.83 for PGY-2, and 3.99 for PGY-3; P &lt; .01 for PGY-1 versus PGY-3). Significantly different means by trainee level were noted across 21 subcompetencies on milestone-based assessments (P &lt; .01 for PGY-1 versus PGY-3). Conclusions Initial results indicate milestone-based assessments stratify trainee performance by level better than Likert-type assessments. Average PGY-level scores from milestone-based assessments may ultimately provide guidance for determining whether trainees are progressing at the expected pace.
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Setiawati, Farida Agus, Djemari Mardapi, and Saifuddin Azwar. "PENSKALAAN TEORI KLASIK INSTRUMEN MULTIPLE INTELLIGENCES TIPE THURSTONE DAN LIKERT." Jurnal Penelitian dan Evaluasi Pendidikan 17, no. 2 (December 15, 2013): 259–74. http://dx.doi.org/10.21831/pep.v17i2.1699.

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Penelitian ini bertujuan untuk: 1) mengetahui hasil penskalaan instrumen multiple intelligences (MI) pada tipe Thurstone dan Likert dengan pendekatan klasik, 2) mengetahui karakteristik instrument MI pada tipe Thurstone dan Likert pada data asli dan data yang diskalakan, 3) membandingkan karakteristik psikometrik pada kedua tipe data yang sudah diskalakan. Penelitian ini menggunakan pendekatan kuantitatif yang pelaksanaannya terdiri dari empat bagian yang saling terkait, yaitu penelitian pengembangan instrumen, penskalaan pada data hasil ujicoba, analisis karakteristik psikometrik instrumen, dan perbandingan karakteristik psikometrik instrumen. Instrumen dikembangkan menggunakan tipe Thurstone dan Likert pada konstruk yang sama. Perbandingan karakteristik psikometrik kedua instrumen dilakukan secara diskriptif. Hasil penskalaan dengan metode paired comparison didapatkan urutan skor stimulus dari yang terendah yaitu: logika matematika, musik, linguistik, kinestetik, naturalis, visual, interpersonal, eksistensial dan intrapersonal. Penskalaan dengan metode summated rating dihasilkan skor terstandar dari yang rendah hingga tinggi pada tiap respons. Terdapat perubahan skor, varian, reliabilitas dan kesalahan baku pengukuran (SEM) dari data asli dengan data yang diskalakan. Koefisien reliabilitas dan SEM instrumen tipe Thurstone lebih rendah dibanding tipe Likert. Kata kunci: penskalaan, multiple intelligences, tipe Thurstone, tipe Likert ______________________________________________________________SCALING CLASSICAL THEORY OF MULTIPLE INTELLIGENCES CLASSICAL INSTRUMENT TYPE THURSTONE AND LIKERTAbstract The study aimed to: 1) result the scaling data of multiple intelligence (MI) instruments of Thurstone and Likert types using the classical approach, 2) reveal the psychometric characteristics of Thurstone and Likert types in the original data and the scaled data, 3) compare the psychometric characteristics of the two types of data. The study used the quantitative research approach. The activity consisted of: developing instruments, processing the data scaling, analyzing the psychometric characteristics of the instruments, and comparing the psychometric characteristics of them. The instrument was developed using Thurstone and Likert types in the same constructs. The comparison of psychometric characteristics of two types of data was analyzed by descriptive statistic. The result of scaling using paired comparison method are the sequential scores from a low to high on mathematical-logical, musical, linguistic, kinesthetic, natural, visual, interpersonal, existential and intrapersonal inteligence. The scaling using summated rating produce scores that vary in each response. There are changes of variants and standard error of measurement (SEM) after transformed data. The reliability and SEM of the Thurstone type are lower than that of Likert type.Keywords: scaling, multiple intelligence instrument, Thurstone type, Likert type
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36

Capuano, Ana W., Jeffrey D. Dawson, Marizen R. Ramirez, Robert S. Wilson, Lisa L. Barnes, and R. William Field. "Modeling Likert Scale Outcomes With Trend-Proportional Odds With and Without Cluster Data." Methodology 12, no. 2 (April 2016): 33–43. http://dx.doi.org/10.1027/1614-2241/a000106.

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Abstract. Likert scales are commonly used in epidemiological studies employing surveys. In this tutorial we demonstrate how the proportional odds model and the trend odds model can be applied simultaneously to data measured in Likert scales, allowing for random cluster effects. We use two datasets as examples: an epidemiological study on aging and cognition among community-dwelling Black persons, and a clustered large survey data from 28,882 students in 81 middle schools. The first example models the Likert outcome from the question: “People act as if they think you are dishonest.” The trend-proportional odds model indicates that Black men have higher odds than Black women of reporting being perceived as dishonest. The second example models the Likert outcome from the question: “How often have you been beaten up at school?”. The trend-proportional odds model indicates that children with disability have a higher odds of severe violence than other children. For both examples, the cumulative odds ratio increases by more than 60% at the higher Likert levels.
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Carifio, James, and Rocco J. Perla. "Ten Common Misunderstandings, Misconceptions, Persistent Myths and Urban Legends about Likert Scales and Likert Response Formats and their Antidotes." Journal of Social Sciences 3, no. 3 (March 1, 2007): 106–16. http://dx.doi.org/10.3844/jssp.2007.106.116.

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38

Retnawati, Heri. "Proving content validity of self-regulated learning scale (The comparison of Aiken index and expanded Gregory index)." Research and Evaluation in Education 2, no. 2 (December 28, 2016): 155. http://dx.doi.org/10.21831/reid.v2i2.11029.

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This study aims to prove the content validity of the self-regulated learning (SRL) scale using Likert model and multiple-choice model with content validity coefficient based on expert assessments with Aiken formula and expanded Gregory formula. In this study, the SRL scale with Likert and multiple-choice model are developed using the same outline/format. There are three experts who assess the items' relevancy using indicators of both scale formats. The results of the expert assessments are then used to calculate the coefficient of the validity with Aiken formula and the expanded Gregory formula. The results showed that the content validity coefficient based on expert assessment on Likert and multiple-choice format with Aiken formula is at 0.9 for each, while using the Aiken formula and expanded Gregory formula, the coefficient is 0.6 for Likert, and 0.8 for multiple-choice.
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39

Sullivan, Gail M., and Anthony R. Artino. "Analyzing and Interpreting Data From Likert-Type Scales." Journal of Graduate Medical Education 5, no. 4 (December 1, 2013): 541–42. http://dx.doi.org/10.4300/jgme-5-4-18.

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40

Royeen, Charlotte Brasic. "Adaptation of Likert Scaling for Use with Children." Occupational Therapy Journal of Research 5, no. 1 (January 1985): 59–69. http://dx.doi.org/10.1177/153944928500500104.

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41

Maeda, Hotaka. "Response option configuration of online administered Likert scales." International Journal of Social Research Methodology 18, no. 1 (February 7, 2014): 15–26. http://dx.doi.org/10.1080/13645579.2014.885159.

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42

Asún, Rodrigo A., Karina Rdz-Navarro, and Jesús M. Alvarado. "Developing Multidimensional Likert Scales Using Item Factor Analysis." Sociological Methods & Research 45, no. 1 (January 13, 2015): 109–33. http://dx.doi.org/10.1177/0049124114566716.

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43

Chang, Lei. "Dependability of Anchoring Labels of Likert-Type Scales." Educational and Psychological Measurement 57, no. 5 (October 1997): 800–807. http://dx.doi.org/10.1177/0013164497057005005.

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44

Camparo, James, and Lorinda B. Camparo. "The Analysis of Likert Scales Using State Multipoles." Journal of Educational and Behavioral Statistics 38, no. 1 (February 2013): 81–101. http://dx.doi.org/10.3102/1076998611431084.

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45

Maurer, Todd J., and Kimberly D. Andrews. "Traditional, Likert, and Simplified Measures of Self-Efficacy." Educational and Psychological Measurement 60, no. 6 (December 2000): 965–73. http://dx.doi.org/10.1177/00131640021970899.

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46

Weng, Li-Jen, and Chung-Ping Cheng. "Effects of Response Order on Likert-Type Scales." Educational and Psychological Measurement 60, no. 6 (December 2000): 908–24. http://dx.doi.org/10.1177/00131640021970989.

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Wakita, Takafumi, Natsumi Ueshima, and Hiroyuki Noguchi. "Psychological Distance Between Categories in the Likert Scale." Educational and Psychological Measurement 72, no. 4 (January 12, 2012): 533–46. http://dx.doi.org/10.1177/0013164411431162.

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48

Seval; TOKER, DÖNMEZ. "Construction of a likert-type transformational Leadership Scale." Ankara Üniversitesi Dil ve Tarih-Coğrafya Fakültesi Dergisi - DTCF Dergisi 57, no. 2 (2017): 753–75. http://dx.doi.org/10.1501/dtcfder_0000001537.

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49

Robertson, Judy. "Likert-type scales, statistical methods, and effect sizes." Communications of the ACM 55, no. 5 (May 2012): 6–7. http://dx.doi.org/10.1145/2160718.2160721.

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50

Wadgave, Umesh, and Mahesh R. Khairnar. "Parametric tests for Likert scale: For and against." Asian Journal of Psychiatry 24 (December 2016): 67–68. http://dx.doi.org/10.1016/j.ajp.2016.08.016.

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