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R语言 rockchalk包 testSlopes()函数中文帮助文档(中英文对照)

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发表于 2012-9-27 22:45:41 | 显示全部楼层 |阅读模式
testSlopes(rockchalk)
testSlopes()所属R语言包:rockchalk

                                        Hypothesis tests for Simple Slopes Objects
                                         简单的斜坡对象的假设检验

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

The user must first run plotSlopes, and then supply that output object to this function.
用户必须先运行plotSlopes,然后提供给该函数的输出对象。


用法----------Usage----------


  testSlopes(plotSlopesObject)



参数----------Arguments----------

参数:plotSlopesObject
Output from the plotSlopes function
输出plotSlopes功能


Details

详细信息----------Details----------

Consider a regression, for example
例如考虑的回归,

y <- b0 + b1*x1 + b2*x2 + b3*(x1*x2) + b4*x3 + ... + error
Y < -  B0 + B1 * X1 + B2 * X2 + B3 *(X1 * X2)+ B4 * X3 + ... +错误

If plotSlopes has been run with the variable plotx="x1" and the variable modx="x2", then there will be several plotted lines, one for various values of x2.  We wonder if the combined effect of x1 is statistically significantly different from 0 for each of those values of x2.
如果plotSlopes已运行的变量plotx =“X1”和变量MODx的“X2”,然后会有几个绘制线,为不同值的2倍。我们不知道,如果合并后的效果X1是统计显着不为0,每个值的2倍。

This function performs a test of the null hypothesis of the slope of each fitted line in a plotSlopes object is statistically significant from zero. A simple t-test for each line is offered. No correction for the conduct of multiple hypothesis tests (no Bonferroni correction).
此功能进行测试的零假设每个拟合线的斜率在plotSlopes对象,从零是统计上显着。提供一个简单的t检验的每一行。不必对多个假设检验的行为(没有Bonferroni校正)。

In addition, the so-called Johnson-Neyman (Johnson-Neyman, 1936; Preacher, Curran, and Bauer, 2006) interval is calculated and a couple of efforts are made to render it graphically.  Where the t-test considers the question, is the slope of the line (b1 + b3*x2) different from 0, the J-N approach asks "for which values of x2 will that plotted line be statistically significant.
此外,所谓的约翰逊,的奈曼·约翰逊·奈曼,1936年,传道者的柯伦,和Bauer,2006年的间隔计算,一对夫妇的努力图形方式呈现。 t检验考虑的问题,是直线的斜率(B1 + B3 * X2)从0不同,JN方法要求“X2将其值绘制线在统计上显着。”


值----------Value----------

A list including the hypothesis test table. For numeric modx variables, also the Johnson-Neyman (J-N) interval boundaries.
一个列表,其中包括假设检验表。对于数字MODx的变量,也是约翰逊 - 奈曼(JN)区间的边界。


(作者)----------Author(s)----------



Paul E. Johnson &lt;pauljohn@ku.edu&gt;




参考文献----------References----------

Daniel J. (2006). Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis. Journal of Educational and Behavioral Statistics. 31,4, 437-448.
linear hypotheses and their applications to some educational problems. Statistical Research Memoirs, 1, 57-93.

参见----------See Also----------

plotSlopes
plotSlopes


实例----------Examples----------


library(car)
m3 <- lm(statusquo ~ income * sex, data = Chile)
m3ps <-plotSlopes(m3, modx = "sex", plotx = "income")
testSlopes(m3ps)

m4 <- lm(statusquo ~ region * income, data= Chile)
m4ps <- plotSlopes(m4, modx = "region", plotx = "income", plotPoints = FALSE)
testSlopes(m4ps)


m5 <- lm(statusquo ~ region * income + sex + age, data= Chile)
m5ps <- plotSlopes(m5, modx = "region", plotx = "income")
testSlopes(m5ps)

m6 <- lm(statusquo ~ income * age + education + sex + age, data=Chile)
m6ps <- plotSlopes(m6, modx = "income", plotx = "age")
testSlopes(m6ps)

## Finally, if model has no relevant interactions, testSlopes does nothing.[#最后,如果模型没有相关的相互作用,testSlopes什么都不做。]
m9 <- lm(statusquo ~ age + income * education + sex + age, data=Chile)
m9ps <- plotSlopes(m9, modx = "education", plotx = "age", plotPoints = FALSE)
testSlopes(m9ps)

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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