Temporal Dominance of Sensations (TDS) and Temporal Check-All-That-Apply (TCATA) make it possible to capture temporal changes in the perception of sensory attributes within a product. However, temporal measurements bring new sources of uncontrolled variability that can make them imprecise, particularly with consumer panels. This article aims to demonstrate the importance of considering this imprecision when interpreting temporal data. First, the levels of imprecision due to non-repeatability or disagreement were assessed. The precision of TDS and TCATA was shown to be low, mainly due to disagreement caused by high heterogeneity in total durations of perception. Then, a new framework of analysis has been introduced. It allowed testing of differences in the median times of selection or unselection of attributes. A new representation of TDS and TCATA data has been proposed to visualize and objectify uncertainty in periods of perception. The conclusions obtained with the new framework were compared to those obtained with the usual analyses based on the evolution of citation rates over time. It was shown that the interpretation of TDS/TCATA curves and difference curves can be tricky without guidelines regarding the minimum size of differences that can be considered significant and interpretable. Finally, it was shown that the temporal resolution of the methods was about 10% of the total duration of the perception. These findings question the ability of TDS and TCATA to capture subtle temporal differences. Therefore, recommendations were made for interpreting temporal data in a way that robust conclusions can be drawn.

中文翻译：

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消费者使用的 TDS 和 TCATA 的时间精度和分辨率

感觉的时间主导 (TDS) 和应用时间检查 (TCATA) 可以捕获产品内感官属性感知的时间变化。然而，时间测量带来了不受控制的变化的新来源，这可能使测量变得不精确，特别是对于消费者面板。本文旨在证明在解释时态数据时考虑这种不精确性的重要性。首先，评估由于不可重复性或不一致而导致的不精确程度。 TDS和TCATA的精度较低，主要是由于感知总持续时间的高度异质性导致的不一致。然后，引入了新的分析框架。它允许测试选择或取消选择属性的中值时间的差异。人们提出了 TDS 和 TCATA 数据的新表示形式，以可视化和客观化感知时期的不确定性。将使用新框架获得的结论与基于引用率随时间变化的常规分析获得的结论进行比较。结果表明，如果没有关于可被视为显着且可解释的差异的最小大小的指导原则，TDS/TCATA 曲线和差异曲线的解释可能会很棘手。最后，结果表明，该方法的时间分辨率约为感知总持续时间的 10%。这些发现质疑 TDS 和 TCATA 捕捉细微时间差异的能力。因此，建议以能够得出可靠结论的方式解释时间数据。