pyears(survival)
pyears()所属R语言包：survival
Person Years
人年
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function computes the person-years of follow-up time contributed by a cohort of subjects, stratified into subgroups. It also computes the number of subjects who contribute to each cell of the output table, and optionally the number of events and/or expected number of events in each cell.
此函数计算队列的科目，将分组分层贡献的人 - 年随访时间。它还计算科目有助于输出表中的每一个单元，并选择性的事件数量和/或预期的每个单元中的事件数量。
用法----------Usage----------
pyears(formula, data, weights, subset, na.action, rmap,
ratetable, scale=365.25, expect=c('event', 'pyears'),
model=FALSE, x=FALSE, y=FALSE, data.frame=FALSE)
参数----------Arguments----------
参数：formula
a formula object. The response variable will be a vector of follow-up times for each subject, or a Surv object containing the survival time and an event indicator. The predictors consist of optional grouping variables separated by + operators (exactly as in survfit), time-dependent grouping variables such as age (specified with tcut), and optionally a ratetable term. This latter matches each subject to his/her expected cohort.
一个公式对象。响应变量将是一个向量，每个科目的后续倍或Surv对象，其中包含的生存时间和事件指示器。包括可选的+运算符分隔的分组变量的预测（完全一样survfit），随时间变化的，如年龄（指定用tcut）和可选的ratetable长期的分组变量。后者匹配每个受他/她预期的队列。
参数：data
a data frame in which to interpret the variables named in the formula, or in the subset and the weights argument.
在其中解释formula或subset和weights参数命名的变量的数据框。
参数：weights
case weights.
的情况下重量。
参数：subset
expression saying that only a subset of the rows of the data should be used in the fit.
表达说，只有一个数据行的一个子集，应适合使用。
参数：na.action
a missing-data filter function, applied to the model.frame, after any subset argument has been used. Default is options()$na.action.
丢失的数据过滤功能，适用于subset参数已使用的任何model.frame后，。默认options()$na.action。
参数：rmap
an optional list that maps data set names to the ratetable names. See the details section below.
一个可选列表，地图数据设置的ratetable名称命名。见下面的细节部分。
参数：ratetable
a table of event rates, such as survexp.uswhite.
事件的发生率，如survexp.uswhite表。
参数：scale
a scaling for the results. As most rate tables are in units/day, the default value of 365.25 causes the output to be reported in years.
为扩大的结果。由于大多数费率表单位/日，输出的默认值365.25原因被报道多年。
参数：expect
should the output table include the expected number of events, or the expected number of person-years of observation. This is only valid with a rate table.
输出表中应包括预期的事件的数量，或预计数人年观察。这是只用率表有效。
参数：data.frame
return a data frame rather than a set of arrays.
返回一个数据框，而不是一组阵列。
参数：model, x, y
If any of these is true, then the model frame, the model matrix, and/or the vector of response times will be returned as components of the final result.
如果这些是真的，那么模型的框架，模型矩阵，和/或响应时间的向量将返回作为最终结果的组成部分。
Details
详情----------Details----------
Because pyears may have several time variables, it is necessary that all of them be in the same units. For instance, in the call
pyears因为可能有几个时间变量，它是必要的，他们都在相同的单位。例如，在通话
值----------Value----------
a list with components:
一个组件的列表：
参数：pyears
an array containing the person-years of exposure. (Or other units, depending on the rate table and the scale). The dimension and dimmanes of the array correspond to the variables on the right hand side of the model equation.
一个数组，包含暴露的人年。 （或其他单位，对税率表和规模而定）。阵列的维度和dimmanes对应的模型方程右边的变量。
参数：n
an array containing the number of subjects who contribute time to each cell of the pyears array.
一个数组，包含的主题作出贡献时间pyears阵列的每个单元的数量。
参数：event
an array containing the observed number of events. This will be present only if the response variable is a Surv object.
一个数组，包含观察到的事件。这将是目前的，只有当响应变量是一个Surv对象。
参数：expected
an array containing the expected number of events (or person years if expect ="pyears"). This will be present only if there was a ratetable term.
一个数组，包含预期的事件数量（或个人，如果expect ="pyears"）。这将是目前只，如果有一个ratetable长期。
参数：data
if the data.frame option was set, a data frame containing the variables n, event, pyears and event that supplants the four arrays listed above, along with variables corresponding to each dimension. There will be one row for each cell in the arrays.
如果data.frame选项设置，数据框包含的变量n，event，pyears和event，取代上面列出的四个数组，沿每个维度对应的变量。会有一个阵列中的每个单元格的行。
参数：offtable
the number of person-years of exposure in the cohort that was not part of any cell in the pyears array. This is often useful as an error check; if there is a mismatch of units between two variables, nearly all the person years may be off table.
数人暴露在队列，这不是pyears阵列中的任何单元格的一部分。这往往是有用的错误检查;如果有一个单位的两个变量之间的不匹配，几乎所有的人几年可能关闭表。
参数：summary
a summary of the rate-table matching. This is also useful as an error check.
率表匹配的总结。错误检查，这也是有用的。
参数：call
an image of the call to the function.
调用函数的图像。
参数：na.action
the na.action attribute contributed by an na.action routine, if any.
na.action属性na.action常规，如果任何贡献。
参见----------See Also----------
ratetable, survexp, Surv.
ratetable，survexp，Surv。
举例----------Examples----------
# Look at progression rates jointly by calendar date and age[由日历日期和年龄看进展率]
# []
temp.yr <- tcut(mgus$dxyr, 55:92, labels=as.character(55:91))
temp.age <- tcut(mgus$age, 34:101, labels=as.character(34:100))
ptime <- ifelse(is.na(mgus$pctime), mgus$futime, mgus$pctime)
pstat <- ifelse(is.na(mgus$pctime), 0, 1)
pfit <- pyears(Surv(ptime/365.25, pstat) ~ temp.yr + temp.age + sex, mgus,
data.frame=TRUE)
# Turn the factor back into numerics for regression[回转动因素回归数值计算]
tdata <- pfit$data
tdata$age <- as.numeric(as.character(tdata$temp.age))
tdata$year<- as.numeric(as.character(tdata$temp.yr))
fit1 <- glm(event ~ year + age+ sex +offset(log(pyears)),
data=tdata, family=poisson)
## Not run: [＃无法运行：]
# fit a gam model [适合GAM模型]
gfit.m <- gam(y ~ s(age) + s(year) + offset(log(time)),
family = poisson, data = tdata)
## End(Not run)[＃结束（不运行）]
# Example #2 Create the hearta data frame: [例如＃2创建的hearta数据框：]
hearta <- by(heart, heart$id,
function(x)x[x$stop == max(x$stop),])
hearta <- do.call("rbind", hearta)
# Produce pyears table of death rates on the surgical arm[手术手臂上产生pyears表的死亡率]
# The first is by age at randomization, the second by current age[首先是在随机的年龄，由目前的年龄第二]
fit1 <- pyears(Surv(stop/365.25, event) ~ cut(age + 48, c(0,50,60,70,100)) +
surgery, data = hearta, scale = 1)
fit2 <- pyears(Surv(stop/365.25, event) ~ tcut(age + 48, c(0,50,60,70,100)) +
surgery, data = hearta, scale = 1)
fit1$event/fit1$pyears #death rates on the surgery and non-surg arm[手术和非外科手臂上的死亡率]
fit2$event/fit2$pyears #death rates on the surgery and non-surg arm[手术和非外科手臂上的死亡率]
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 2012-2-16 18:13:18
