Abstract：
BACKGROUND: Parametric regression analysis is widely used in methods comparisons and more recently in checking the concordance of test results following receipt of new reagent lots. The greater frequency of reagent-lot evaluations increases pressure to detect bias with smallest possible sample sizes (i.e. smallest consumption of time and resources). This study revisits bias detection using the joint slope, intercept confidence region as an alternative to slope and intercept confidence intervals.
METHODS: Four cases were considered representing constant errors, proportional errors (constant CV) and two more complicated error patterns typical of immunoassays. Maximum:minimum range ratios varied from 2:1 to 2000:1. After setting a maximum tolerable difference a series of slope, intercept combinations, each of which predicted the critical difference, were systematically evaluated in simulations which determined the minimum sample size required to detect the difference, firstly using slope, intercept confidence intervals and secondly using the joint slope, intercept confidence region.
RESULTS: At small to moderate range ratios, bias detection by joint confidence region required greatly reduced sample sizes to the extent that it should encourage reagent-lot evaluations or, alternatively, transform those already routinely performed into considerably less costly exercises.
CONCLUSIONS: While some software is available to calculate joint confidence regions in real-life analyses, shifting this testing method into the mainstream will require a greater number of software developers incorporating the necessary code into their regression programs. The computer program used to conduct this study is freely available and can be used to model any laboratory test.
METHODS: Four cases were considered representing constant errors, proportional errors (constant CV) and two more complicated error patterns typical of immunoassays. Maximum:minimum range ratios varied from 2:1 to 2000:1. After setting a maximum tolerable difference a series of slope, intercept combinations, each of which predicted the critical difference, were systematically evaluated in simulations which determined the minimum sample size required to detect the difference, firstly using slope, intercept confidence intervals and secondly using the joint slope, intercept confidence region.
RESULTS: At small to moderate range ratios, bias detection by joint confidence region required greatly reduced sample sizes to the extent that it should encourage reagent-lot evaluations or, alternatively, transform those already routinely performed into considerably less costly exercises.
CONCLUSIONS: While some software is available to calculate joint confidence regions in real-life analyses, shifting this testing method into the mainstream will require a greater number of software developers incorporating the necessary code into their regression programs. The computer program used to conduct this study is freely available and can be used to model any laboratory test.
摘要：
背景：参数回归分析广泛用于方法比较，最近用于检查收到新试剂批次后的测试结果的一致性。试剂批次评估的更高频率增加了以最小可能的样本大小(即,时间和资源的最小消耗)检测偏差的压力。这项研究重新审视了使用联合斜率的偏差检测，截距置信区间作为斜率和截距置信区间的替代方案。
方法：四例被认为是持续错误，比例误差（恒定CV）和两个更复杂的错误模式典型的免疫测定。最大：最小范围比从2：1变化到2000：1。在设置一系列斜率的最大容许差后，截距组合，每个都预测了关键的差异，在模拟中进行了系统评估，确定了检测差异所需的最小样本量，首先使用斜坡，截距置信区间，其次使用联合斜率，截获置信区。
结果：在小到中等范围比率下，通过联合置信区域进行的偏倚检测需要大大减少样本量，以鼓励试剂批次评估或，或者，将那些已经例行进行的练习转变为成本相当低的练习。
结论：虽然一些软件可用于计算现实生活分析中的联合置信区域，将这种测试方法转变为主流将需要更多的软件开发人员将必要的代码整合到他们的回归程序中。用于进行这项研究的计算机程序是免费提供的，可用于模拟任何实验室测试。
方法：四例被认为是持续错误，比例误差（恒定CV）和两个更复杂的错误模式典型的免疫测定。最大：最小范围比从2：1变化到2000：1。在设置一系列斜率的最大容许差后，截距组合，每个都预测了关键的差异，在模拟中进行了系统评估，确定了检测差异所需的最小样本量，首先使用斜坡，截距置信区间，其次使用联合斜率，截获置信区。
结果：在小到中等范围比率下，通过联合置信区域进行的偏倚检测需要大大减少样本量，以鼓励试剂批次评估或，或者，将那些已经例行进行的练习转变为成本相当低的练习。
结论：虽然一些软件可用于计算现实生活分析中的联合置信区域，将这种测试方法转变为主流将需要更多的软件开发人员将必要的代码整合到他们的回归程序中。用于进行这项研究的计算机程序是免费提供的，可用于模拟任何实验室测试。
