discrimSS(sensR)
discrimSS()所属R语言包:sensR
Sensory discrimination sample size calculation
感官歧视样本量的计算
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Computes the sample size for a difference or similarity test for a sensory discrimination experiment using the binomial distribution. The function returns the smallest sample size for the test that gives the at least the desired target-power for the one-sided exact binomial test. A normal approximation to the sample size / power may used. d.primeSS is a convenience function that calls discrimSS but has arguments in terms of d-prime rather than pd, the probability of discrimination.
计算样本大小的感官鉴别实验采用二项式分布的差异或相似的测试。该函数返回的最小样本量的测试,让至少期望的目标功率为片面的精确二项式测试。一个正常的近似的样本大小/电源使用。 d.primeSS是一个方便的功能,调用discrimSS但是有论据,而不是歧视的概率PD,D-首要。
用法----------Usage----------
discrimSS(pdA, pd0 = 0, target.power = 0.90, alpha = 0.05,
pGuess = 1/2, test = c("difference", "similarity"),
statistic = c("exact", "normal"))
d.primeSS(d.primeA, d.prime0 = 0, target.power = 0.90, alpha = 0.05,
method = c("duotrio", "threeAFC", "twoAFC", "triangle"),
test = c("difference", "similarity"),
statistic = c("exact", "normal"))
参数----------Arguments----------
参数:pdA
the probability of discrimination for the model under the alternative hypothesis; scalar between zero and one
标零和一之间的概率备择假设下的模型的歧视;
参数:d.primeA
d-prime for the model under the alternative hypothesis; non-negative numerical scalar
D-黄金备择假设下的模型非负数值标
参数:pd0
the probability of discrimination under the null hypothesis; scalar between zero and one
标零和一之间歧视的零假设下的概率;
参数:d.prime0
d-prime under the null hypothesis; non-negative numerical scalar
D-黄金的零假设下非负数值标
参数:target.power
the desired power for the test
所需的功率测试
参数:alpha
the type I level of the test; scalar between zero and one
I型水平的测试;零和一之间的标量
参数:method
the discrimination protocol for which the sample size should be computed
协议的样本量应计算的歧视
参数:pGuess
the guessing probability for the discrimination protocol, e.g. 1/2 for duo-trio and 2-AFC, and 1/3 for triangle and 3-AFC; scalar between zero and one
猜测概率歧视的协议,例如1/2的二重奏三重奏,以及2-AFC,和1/3为三角形和3-AFC;零和一之间的标量
参数:test
the type of one-sided binomial test (direction of the alternative hypothesis): "difference" corresponds "greater" and "similarity" corresponds to "less"
片面二项式测试方向(替代的假设):“差异”的类型的对应“大于”和“相似性”,对应于“少”
参数:statistic
should sample size calculation be based on the 'exact' binomial test or the normal approximation to this?
样本量的计算应根据“精确”的二项测试或正常的近似?
Details
详细信息----------Details----------
The sample size of the standard one-tailed difference test where the null hypothesis of "no difference" is obtained with pd0 = 0.
样品大小的标准单尾差获得pd0 = 0测试的零假设“没有差别”。
The probability under the null hypothesis is given by pd0 + pg * (1 - pd0) where pg is the guessing probability pGuess. Similarly, the probability of the alternative hypothesis is given by pdA + pg * (1 - pdA)
的零假设下的概率pd0 + pg * (1 - pd0)其中pg是猜测概率pGuess。同样,替代的假设的概率由下式给出pdA + pg * (1 - pdA)
The sample size for the 'exact' test, the function uses the normal approximation to get a starting value for an iterative search. If the sample size based on the normal approximation is larger than 10,000, the function returns the normal approximation and issues a warning.
“精确”测试的样本大小,功能使用正常的逼近,得到一个初始值,迭代搜索。如果样本大小正常近似的基础上大于10000,则函数返回正常的近似,并发出警告。
值----------Value----------
The sample size; a scalar integer.
样本大小的标量整数。
(作者)----------Author(s)----------
Per Bruun Brockhoff and Rune Haubo B Christensen
参考文献----------References----------
models for sensory discrimination tests as generalized linear models.
参见----------See Also----------
AnotA, discrimPwr,
AnotA,discrimPwr,
实例----------Examples----------
## Finding the smallest necessary sample size:[#查找所需的样本量最小的:]
discrimSS(pdA = 0.5, pd0 = 0, target.power = 0.80, alpha = 0.05,
pGuess = 1/2, test = "difference", statistic = "exact")
## Give identical results:[#给相同的结果:]
pd <- coef(rescale(d.prime = 1, method = "twoAFC"))$pd
discrimSS(pdA = pd, pd0 = 0, target.power = 0.90, alpha = 0.05,
pGuess = 1/2, test = "difference", statistic = "exact")
d.primeSS(1, target.power = 0.90, method = "twoAFC")
## A similarity example:[#A相似的例子:]
discrimSS(pdA = 0.1, pd0 = 0.2, target.power = 0.80, alpha = 0.05,
pGuess = 1/2, test = "similarity", statistic = "exact")
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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