Ceiling and floor effects are often observed in social and behavioral science. The current study examines ceiling/floor effects in the context of the t-test and ANOVA, two frequently used statistical methods in experimental studies. Our literature review indicated that most researchers treated ceiling or floor data as if these data were true values, and that some researchers used statistical methods such as discarding ceiling or floor data in conducting the t-test and ANOVA. The current study evaluates the performance of these conventional methods for t-test and ANOVA with ceiling or floor data. Our evaluation also includes censored regression with regard to its capacity for handling ceiling/floor data. Furthermore, we propose an easy-to-use method that handles ceiling or floor data in t-tests and ANOVA by using properties of truncated normal distributions. Simulation studies were conducted to compare the performance of the methods in handling ceiling or floor data for t-test and ANOVA. Overall, the proposed method showed greater accuracy in effect size estimation and better-controlled Type I error rates over other evaluated methods. We developed an easy-to-use software package and web applications to help researchers implement the proposed method. Recommendations and future directions are discussed.

在社会和行为科学中经常观察到天花板和地板的影响。当前的研究在t检验和方差分析（ANOVA）的背景下研究了天花板/地板的影响，这是实验研究中两种常用的统计方法。我们的文献综述表明，大多数研究人员将上限或下限数据视为真实值，而有些研究人员在进行t检验和ANOVA时使用了统计方法，例如丢弃上限或下限数据。当前的研究评估了这些传统方法对t的性能-test和带有天花板或地板数据的方差分析。我们的评估还包括审查处理上限/下限数据的能力的回归。此外，我们提出了一种易于使用的方法，该方法通过使用截断正态分布的属性来处理t检验和ANOVA中的天花板或地板数据。进行了仿真研究，以比较该方法在处理t检验和ANOVA的天花板或地板数据中的性能。总体而言，与其他评估方法相比，该方法在效果大小估计方面显示出更高的准确性，并且I类错误率得到了更好的控制。我们开发了易于使用的软件包和Web应用程序，以帮助研究人员实施所提出的方法。讨论了建议和未来方向。