multreg(rpsychi)
multreg()所属R语言包:rpsychi
A multiple regression analysis using individual data
使用个人数据的多元回归分析
译者:生物统计家园网 机器人LoveR
描述----------Description----------
multreg conducts a multiple regression analysis using individual data.
multreg使用单独的数据进行多元回归分析。
用法----------Usage----------
multreg(formula, data, sig.level = 0.05, digits = 3)
参数----------Arguments----------
参数:formula
two-sided formula; the left-hand-side of which gives one dependent variable containing a numeric variable, and the right-hand-side of several independent variables containing a numeric variable
两个双面公式;的左手侧,它给出了一个含有一个数字变量的因变量,和右手侧的几个独立的变量,包含一个数字变量
参数:data
a data frame contains the variables in the fomrmula
数据框包含的变量在fomrmula
参数:sig.level
a numeric contains the significance level (default 0.05)
一个数字的显着性水平(默认0.05)
参数:digits
the specified number of decimal places (default 3)
指定的小数位数(默认为3)
Details
详细信息----------Details----------
This function conducts a multiple regression analysis using individual data. The dependent variable and independent variables should be a numeric vector. In this function, you cannot specify any interaction nor any curvilinear effect. Statistical power is calculated using the following specifications:
此功能使用单独的数据进行多元回归分析。因变量和自变量应该是一个数值向量。在这个函数中,你可以不指定任何互动,也没有任何曲线的效果。统计功率的计算使用以下规范:
(a) small (R^{2} = 0.02), medium (R^{2} = 0.13), and large (R^{2} = 0.26) population effect sizes, according to the interpretive guideline for effect sizes by Cohen (1992)
(一)小(R^{2} = 0.02),中(R^{2} = 0.13),和大(R^{2} = 0.26)人口影响的大小,根据解释性指引,影响的大小由Cohen(1992年)
(b) sample size specified by data
(二)样本规模指定的data
(c) significance level specified by sig.level
(三)显着性水平指定的sig.level
(d) numbers of independent variable specified by formula
(四)数字自变量指定的formula
值----------Value----------
参数:samp.stat
returns the means and unbiased standard deviations
返回的手段和公正的标准偏差
参数:corr.partial.corr
returns a product-moment correlation matrix (lower triangle) and a partial correlation matrix given all remaining variables (upper triangle)
返回一个积矩相关系数矩阵(下三角)和部分相关的所有剩余的变量(上三角矩阵)
参数:corr.confidence
returns lower and upper confidence limits (lower and upper triangles, respectively)
下部和上部的置信界限(三角形下部和上部,分别)返回
参数:omnibus.es
returns a coefficient of determination and its' confidence interval
返回系数的决心和信心间隔
参数:raw.estimates
returns partial regression coefficients, their confidence intervals, and standard errors
返回偏回归系数,其置信区间和标准差,
参数:standardized.estimates
returns standardized partial regression coefficients, their confidence intervals, and standard errors
返回标准化偏回归系数的置信区间和标准差,
参数:power
returns statistical power for detecting small (R^{2} = 0.02), medium (R^{2} = 0.13), and large (R^{2} = 0.26) population effect sizes
返回统计功率检测(R^{2} = 0.02),中(R^{2} = 0.13),和大(R^{2} = 0.26)人口影响的大小
(作者)----------Author(s)----------
Yasuyuki Okumura<br>
Department of Social Psychiatry, <br>
National Institute of Mental Health, <br>
National Center of Neurology and Psychiatry <br>
<a href="mailto:yokumura@blue.zero.jp">yokumura@blue.zero.jp</a>
参考文献----------References----------
参见----------See Also----------
multreg.second, samplesize.rsq
multreg.second,samplesize.rsq
实例----------Examples----------
##Cohen (2003) Table 3.5.1[#科恩(2003)表3.5.1]
dat <- data.frame(
salary = c(51876, 54511, 53425, 61863, 52926, 47034, 66432, 61100, 41934,
47454, 49832, 47047, 39115, 59677, 61458, 54528, 60327, 56600,
52542, 50455, 51647, 62895, 53740, 75822, 56596, 55682, 62091,
42162, 52646, 74199, 50729, 70011, 37939, 39652, 68987, 55579,
54671, 57704, 44045, 51122, 47082, 60009, 58632, 38340, 71219,
53712, 54782, 83503, 47212, 52840, 53650, 50931, 66784, 49751,
74343, 57710, 52676, 41195, 45662, 47606, 44301, 58582),
pubs = c(18, 3, 2, 17, 11, 6, 38, 48, 9, 22, 30, 21,
10, 27, 37, 8, 13, 6, 12, 29, 29, 7, 6, 69, 11, 9,
20, 41, 3, 27, 14, 23, 1, 7, 19, 11, 31, 9, 12, 32,
26, 12, 9, 6, 39, 16, 12, 50, 18, 16, 5, 20, 50,
6, 19, 11, 13, 3, 8, 11, 25, 4),
cits = c(50, 26, 50, 34, 41, 37, 48, 56, 19, 29,
28, 31, 25, 40, 61, 32, 36, 69, 47, 29, 35,
35, 18, 90, 60, 30, 27, 35, 14, 56, 50, 25,
35, 1, 69, 69, 27, 50, 32, 33, 45, 54, 47, 29,
69, 47, 43, 55, 33, 28, 42, 24, 31, 27,
83, 49, 14, 36, 34, 70, 27, 28)
)
multreg(salary~ pubs + cits, data=dat)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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