Relative Merits of Nominal and Effective Indexes of Difficulty of Fitts’ Law: Effects of Sample Size and the Number of Repetitions on Model Fit

Yamanaka, Shota

doi:10.1080/10447318.2024.2303201

International Journal of Human–Computer Interaction

2024

DOI: 10.1080/10447318.2024.2303201

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Relative Merits of Nominal and Effective Indexes of Difficulty of Fitts’ Law: Effects of Sample Size and the Number of Repetitions on Model Fit

Shota Yamanaka

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Cited by 2 publications

References 74 publications

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Deciding to Stop Early or Continue the Experiment After Checking p -Values at Interim Points: Introducing Group Sequential Designs to UI-Based Comparative Studies

Yamanaka

2024

International Journal of Human–Computer Interaction

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Deciding to Stop Early or Continue the Experiment After Checking p -Values at Interim Points: Introducing Group Sequential Designs to UI-Based Comparative Studies

Yamanaka

2024

International Journal of Human–Computer Interaction

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Verifying Finger-Fitts Models for Normalizing Subjective Speed-Accuracy Biases

Yamanaka,

Usuba,

Oba

et al. 2024

Proc. ACM Hum.-Comput. Interact.

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Previous studies on the Finger-Fitts law (FFitts law) are lacking in sufficient experiments to verify its inherent potential. Since the FFitts law is originally a modified version of the effective width method to normalize speed-accuracy biases, the model fit would improve if multiple biases were mixed together and the throughputs would be more stable than using the nominal target width. In this study, we conduct an experiment in which participants tap 1D-bar and 2D-circular targets under three subjective biases: balancing the speed and accuracy, emphasizing speed, and emphasizing accuracy when they perform the tasks. The results showed that applying the effective width to Ko et al.'s refined FFitts law, which represents the touch ambiguity with a free parameter, was the most successful in normalizing biases. Reanalyzing another dataset on ray-casting pointing also led to the same conclusion. We thus recommend using Ko et al.'s model with effective width when researchers compare several experimental conditions such as devices and user groups.

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Relative Merits of Nominal and Effective Indexes of Difficulty of Fitts’ Law: Effects of Sample Size and the Number of Repetitions on Model Fit

Cited by 2 publications

References 74 publications

Deciding to Stop Early or Continue the Experiment After Checking p -Values at Interim Points: Introducing Group Sequential Designs to UI-Based Comparative Studies

Deciding to Stop Early or Continue the Experiment After Checking p -Values at Interim Points: Introducing Group Sequential Designs to UI-Based Comparative Studies

Verifying Finger-Fitts Models for Normalizing Subjective Speed-Accuracy Biases

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