mudiff.varknown(SampleSizeMeans)
mudiff.varknown()所属R语言包：SampleSizeMeans
Bayesian sample size determination for differences in normal means when variances are known
贝叶斯样本数的方差已知时，在正常手段的差异
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function mudiff.varknown returns the required sample sizes
函数mudiff.varknown返回所需的样本量
用法----------Usage----------
mudiff.varknown(len, lambda1, n01, lambda2, n02, level = 0.95, equal = TRUE)
参数----------Arguments----------
参数：len
The desired total length of the posterior credible interval for the difference between the two unknown means
所需的总长度之间的差后的置信区间的两个未知的手段
参数：lambda1
The known precision (reciprocal of variance) for the first population
已知的精度（方差的倒数）第一人口
参数：n01
Prior sample size equivalent for the mean for the first population
以前样本量相当于第一人口的平均
参数：lambda2
The known precision (reciprocal of variance) for the second population
该已知的精度（方差的倒数）为所述第二人口
参数：n02
Prior sample size equivalent for the mean for the second population
之前第二人口的平均样本量相当于
参数：level
The desired coverage probability of the posterior credible interval (e.g., 0.95)
所需的覆盖概率后验可信区间（如0.95）
参数：equal
logical. Whether or not the final group sizes (n1, n2) are forced to be equal:<br> <table summary="Rd table"> <tr> <td align="left"> </td><td align="left"></td><td align="left"> when equal = TRUE,</td><td align="left"> final sample sizes n1 = n2;</td> </tr> <tr> <td align="left"> </td><td align="left"></td><td align="left"> when equal = FALSE,</td><td align="left"> final sample sizes (n1, n2) minimize the posterior variance given a total of n1+n2 observations</td> </tr> <tr> <td align="left"> </td> </tr> </table>
逻辑。不管是不是最后一组大小（N1，N2）被迫等于：<BR>表summary="Rd table"> <TR> <td ALIGN="LEFT"> </ TD> <TD对齐=“离开“> </ TD> <TD ALIGN="LEFT">当等于= TRUE，</ TD> <TD ALIGN="LEFT">最后的样本量为n1 = n2的; </ TD> </ TR> <TR> <td ALIGN="LEFT"> </ TD> <TD ALIGN="LEFT"> </ TD> <TD ALIGN="LEFT">当等于= FALSE，</ TD> <TD ALIGN="LEFT">最后样本量（N1，N2）最小化后的方差共N1 + N2的意见</ TD> </ TR> <TR> <td ALIGN="LEFT"> </ TD> </ TR> </ TABLE>
Details
详细信息----------Details----------
Assume that a sample from each of two populations will be collected in order to estimate the difference between two independent normal means when the variances are known. Assume that the means are unknown, but have prior information equivalent to (n01, n02) previous observations, respectively. The function mudiff.varknown returns the required sample sizes to attain the desired length len and coverage probability level for the posterior credible interval for the difference between the two unknown means. <br><br> This function uses a fully Bayesian approach to sample size determination. Therefore, the desired coverages and lengths are only realized if the prior distributions input to the function are used for final inferences. Researchers preferring to use the data only for final inferences are encouraged
假设以估计当方差是已知的两个独立的正常装置之间的差异，将被收集在一个样品从每两个种群。假设的手段是未知的，但有先验信息，相当于以前的意见（N01，N02），分别。函数mudiff.varknown返回所需的样本量，以达到所需的长度len和覆盖概率水平后的置信区间为两个未知的手段之间的区别。参考参考这个函数使用了一个完全贝叶斯方法确定样本量。因此，只有实现所需的覆盖度和长度，如果先验分布输入到函数用于最终推论。鼓励研究人员喜欢使用的数据为最终推断
值----------Value----------
The required sample sizes (n1, n2) for each group given the inputs to the function.
各组所需的样本量（N1，N2）输入的功能。
注意----------Note----------
The sample sizes returned by this function are exact.
这个函数返回的样本大小是准确的。
（作者）----------Author(s)----------
Lawrence Joseph <a href="mailto:lawrence.joseph@mcgill.ca">lawrence.joseph@mcgill.ca</a> and Patrick Belisle
参考文献----------References----------
Bayesian sample size determination for Normal means and differences between Normal means<br>
参见----------See Also----------
mudiff.acc, mudiff.alc, mudiff.modwoc, mudiff.acc.equalvar, mudiff.alc.equalvar, mudiff.modwoc.equalvar, mudiff.mbl.varknown, mudiff.mblacc, mudiff.mblalc, mudiff.mblmodwoc, mudiff.mblacc.equalvar, mudiff.mblalc.equalvar, mudiff.mblmodwoc.equalvar, mudiff.freq, mu.varknown, mu.acc, mu.alc, mu.modwoc, mu.mbl.varknown, mu.mblacc, mu.mblalc, mu.mblmodwoc, mu.freq
mudiff.acc，mudiff.alc，mudiff.modwoc，mudiff.acc.equalvar，mudiff.alc.equalvar，mudiff.modwoc.equalvar，mudiff.mbl.varknown，mudiff.mblacc，mudiff.mblalc，mudiff.mblmodwoc，mudiff.mblacc.equalvar，mudiff.mblalc.equalvar，mudiff.mblmodwoc.equalvar，mudiff.freq，mu.varknown，mu.acc，mu.alc ，mu.modwoc，mu.mbl.varknown，mu.mblacc，mu.mblalc，mu.mblmodwoc，mu.freq
实例----------Examples----------
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-29 21:40:42
