Evaluating the sensitive question methods; recommended Uludag Adjustment for the Crosswise Model

Ahmadian R., ERCAN İ.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.52, sa.12, ss.5759-5772, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 52 Sayı: 12
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1080/03610918.2021.1998531
  • Dergi Adı: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Business Source Elite, Business Source Premier, CAB Abstracts, Compendex, Computer & Applied Sciences, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.5759-5772
  • Anahtar Kelimeler: Sensitive questions, Crosswise, Social desirability bias, Simulation, Randomized response, RANDOMIZED-RESPONSE TECHNIQUE, UNMATCHED COUNT TECHNIQUE, CONFIDENTIALITY ASSURANCES, ONLINE SURVEYS, NONCOMPLIANCE, IMPROVE, WOMEN, RATES
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

Sensitive questions are frequently asked in medical, psychological, and sociological research. In the social science literature, it is widely accepted that when respondents are asked such questions, social desirability bias affects survey research. Different methods in the literature aimed to reduce measurement errors such as social desirability bias and increase the reliability of participants' answers. These methods address the problem to increase the effectiveness of predictions by using indirect questioning techniques. The sensitive question methods evaluated in this study are randomized response technique, grouped answer method, unmatched-count technique, and crosswise model. These methods were evaluated with a comprehensive simulation study. The performances of the methods were evaluated according to the sample size and the sensitive issue prevalence in the hypothetical population. In the second part, in order to reduce the small sample size and low prevalence effect of the crosswise model, the Uludag correction of the crosswise model was proposed in the study. As a result, the crosswise model performs quite well compared to the other methods. In the use of the crosswise model, it is recommended to use the Uludag correction of the model proposed in this study in cases where low prevalence and small samples are studied.