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A sense amplifier detects a small signal and amplifies it to produce a large signal. However, a sensing failure may occur owing to the offset voltage caused by the mismatch of paired transistors in the sense amplifier. Since the yield of a sense amplifier is the strong function of the offset voltage, estimation of the offset voltage and its statistical distribution is critical in designing sense amplifiers. As offset voltage can be assumed to follow a Gaussian distribution, its standard deviation (1-sigma, σOS) can be estimated from a simple variance model for paired transistors. However, owing to secondary effects such as differential charge injection, drain-induced barrier lowering and stack effect, σOS estimated using the variance model deviates from that obtained from statistical (Monte-Carlo) simulation, and the deviation becomes larger as technology scales down. This study analyses secondary effects on the offset voltage in the most commonly used latch-type sense amplifiers and suggests novel σOS estimation model. The proposed model, which considers secondary effects, can accurately estimate σOS even when technology scales down. This study also presents the trend of the influence of secondary effects on the offset voltage with technology scaling.