Should A Rule of Thumb be used to Calculate PLS-SEM Sample Size

Chanta Jhantasana
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Abstract

Partial least square structural equation modeling (PLS-SEM) is more commonly used in marketing research because small sample sizes can be used. The main advantage is that the rule of thumb is often used to determine sample size, but the results may be underpowered. Therefore, appropriate sample size is still required to reach the acquired power of 0.80, which should be adequate to avoid false positive and false adverse effects arising from sample sizes that are too large or too small. This research investigates the impact of different sample sizes on the power of analysis, the effect size, and the significance level of the model fitness and parameter estimation process. Many methods are used to generate study sample sizes, such as minimum R2, ten-time rule, inverse square root method, Marsh et al. method, Soper method, and Yamane method. The rule of thumb methods of minimum R2 and ten-time rule generate sample sizes that are too small and inappropriate for PLS-SEM. However, the findings have shown that PLS-SEM can be effective with small sample sizes, but the sample size should be more significant than that generated by the rule-of –thumb methods. The appropriate sample size for this study was 50, with a power of 0.81 and an effect size (f2) ranging between 0.437 and 0.506.
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应该使用经验法则来计算PLS-SEM样品大小吗
偏最小二乘结构方程模型(PLS-SEM)在市场研究中更常用,因为可以使用小样本量。主要的优点是,经验法则通常用于确定样本量,但结果可能不足。因此,仍然需要适当的样本量来达到0.80的获得幂,这应该足以避免样本量过大或过小而产生的假阳性和假不良反应。本研究探讨了不同样本量对模型适应度和参数估计过程的分析能力、效应大小和显著性水平的影响。产生研究样本量的方法有很多,如最小R2法、十次规则法、平方根反比法、Marsh等法、Soper法、Yamane法等。最小R2和十次规则的经验法则方法产生的样本量太小,不适合PLS-SEM。然而,研究结果表明,PLS-SEM可以在小样本量下有效,但样本量应该比经验法则方法产生的样本量更显著。本研究的合适样本量为50,幂为0.81,效应量(f2)在0.437 ~ 0.506之间。
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