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Related Experiment Video

Updated: Sep 22, 2025

Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking

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Published on: August 6, 2013

Managing missing items in the Fagerström Test for Nicotine Dependence: a simulation study.

Shannon L Gutenkunst^1,2, Melanie L Bell³

¹University of Arizona, Statistics Graduate Interdisciplinary Program, Tucson, AZ, USA. shannonlg@arizona.edu.

BMC Medical Research Methodology

|May 20, 2022

Summary

For the Fagerström Test for Nicotine Dependence (FTND), proration is the most accurate and precise method for handling missing data. However, consider sensitivity analyses if over 10% of FTND data is missing.

Keywords:

Imputation Item level missingness Item nonresponse Missing data Questionnaire Scoring

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Area of Science:

Behavioral Science
Psychometrics
Public Health

Background:

The Fagerström Test for Nicotine Dependence (FTND) is a key tool for assessing nicotine dependence.
Managing missing data in the FTND is crucial for accurate assessment but lacks standardized methods.

Purpose of the Study:

To evaluate various methods for handling missing items within the FTND.
To determine the most accurate and precise imputation techniques for FTND scores.

Main Methods:

A simulation study was conducted using data from the Arizona Smokers' Helpline.
1000 datasets were simulated for different sample sizes and missing data proportions (MAR and MNAR).
Six methods for managing missing FTND items were compared for accuracy and precision.

Main Results:

Proration demonstrated superior accuracy and precision for FTND scores across various missing data scenarios.
Proration's accuracy slightly decreased as the percentage of missing data increased.
At 9% missing data, proration's bias was minimal (-0.3%); at 35% missing data, bias increased to -6%.

Conclusions:

Proration is recommended for managing missing FTND data due to its accuracy, precision, and ease of use.
For datasets with over 10% missing data, a sensitivity analysis using alternative methods is advised.
This research provides practical guidance for researchers using the FTND.