通过 id 创建滞后变量时无法将类型 'closure' 强制转换为类型列表的向量

Question

我想使用我在这个平台上找到的这段代码创建一个 RD_expenses 的滞后变量：

library(data.table)
TandCtable[, RDexp_pre1:=c(NA, "RD_expenses"[-.N]), by=id]

然而，当我运行代码时，我得到这个错误：

Error in as.vector(x, "list") : cannot coerce type 'closure' to vector of type 'list'

可能与数据类型有关，但我不知道是什么。

我需要将滞后变量作为协变量添加到我的固定效应模型中：

m5a <- felm(ihs(RD_expenses) ~ merger_it_pre1 + merger_it + merger_it_post1 + merger_it_post2 + merger_it_post3 + factor(year),
       data = TandC,
       subset = RD_expenses > pcts[1] & RD_expenses < pcts[2])

非常感谢您的帮助！

编辑：抱歉，这是数据table！

structure(list(company = c("ALLERGAN PUBLIC LIMITED COMPANY", 
"ALLERGAN PUBLIC LIMITED COMPANY", "ALLERGAN PUBLIC LIMITED COMPANY", 
"ALLERGAN PUBLIC LIMITED COMPANY", "ALLERGAN PUBLIC LIMITED COMPANY", 
"ALLERGAN PUBLIC LIMITED COMPANY", "ALLERGAN PUBLIC LIMITED COMPANY", 
"ALPINE ELECTRONICS, INC.", "ALPINE ELECTRONICS, INC.", "ALPINE ELECTRONICS, INC.", 
"ALPINE ELECTRONICS, INC.", "ALPINE ELECTRONICS, INC.", "ALPINE ELECTRONICS, INC.", 
"ALPS ALPINE CO.,LTD.", "ALPS ALPINE CO.,LTD.", "ALPS ALPINE CO.,LTD.", 
"ALPS ALPINE CO.,LTD.", "ALPS ALPINE CO.,LTD.", "ALPS ALPINE CO.,LTD.", 
"ANICURA STOCKHOLMS REGIONDJURSJUKHUS AB"), year = c(2013L, 2014L, 
2015L, 2016L, 2017L, 2018L, 2019L, 2015L, 2016L, 2017L, 2018L, 
2019L, 2020L, 2015L, 2016L, 2017L, 2018L, 2019L, 2020L, 2015L
), case_code = c("M.8193", "M.8193", "M.8193", "M.8193", "M.8193", 
"M.8193", "M.8193", "M.8833", "M.8833", "M.8833", "M.8833", "M.8833", 
"M.8833", "M.8833", "M.8833", "M.8833", "M.8833", "M.8833", "M.8833", 
"M.9019"), merger = c(2016, 2016, 2016, 2016, 2016, 2016, 2016, 
2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 
2018, 2018), acquirer = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L), .Label = c("0", 
"1"), class = "factor"), country = c("IE", "IE", "IE", "IE", 
"IE", "IE", "IE", "JP", "JP", "JP", "JP", "JP", "JP", "JP", "JP", 
"JP", "JP", "JP", "JP", "SE"), industry_firm = c(2120, 2120, 
2120, 2120, 2120, 2120, 2120, 6420, 6420, 6420, 6420, 6420, 6420, 
2611, 2611, 2611, 2611, 2611, 2611, 7500), industry_firm_2 = c(21, 
21, 21, 21, 21, 21, 21, 64, 64, 64, 64, 64, 64, 26, 26, 26, 26, 
26, 26, 75), industry_merger = c(4646, 4646, 4646, 4646, 4646, 
4646, 4646, 453, 453, 453, 453, 453, 453, 453, 453, 453, 453, 
453, 453, 1092), industry_merger_2 = c(46, 46, 46, 46, 46, 46, 
46, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 10), simpl_proc = structure(c(2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 1L), .Label = c("0", "1"), class = "factor"), commitments = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L), .Label = c("0", "1"), class = "factor"), cross_border = structure(c(2L, 
2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L), .Label = c("0", "1"), class = "factor"), duration = c(25, 
25, 25, 25, 25, 25, 25, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 
29, 29, 149), employees = c(384, 432, 624, 334, 356, 338, 348, 
1122, 1110, 1492, 1317, NA, NA, 39588, 42053, 42289, 41840, 40443, 
NA, 285), profit_margin = c(-0.14684, -0.85298, -0.58792, -0.38872, 
-1.30312, -0.86866, -0.6363, -1.925, 0.567, 3.984, 4.01, NA, 
NA, 8.763, 6.572, 7.599, 4.838, 1.921, NA, 8.049), RD_expenses = c(8946.414554, 
9977.75638, 43326.90616, 48870.14658, 35022.10866, 39584.25952, 
32259.2173, 6303.95, 6812.46, 14993.39, 21925.5, NA, NA, 259971.9513, 
269457.2012, 227757.0765, 263893.2745, 316285.6753, NA, 7053.5
), sales = c(125844.3945, 111010.5704, 276862.329, 276455.8596, 
265833.4972, 275762.3064, 286432.2966, 1260609.732, 1217111.106, 
1094409.478, 2057945, NA, NA, 6036362.168, 6288047.037, 6560212.444, 
6831502.438, 6806267.552, NA, 27113.77546), period = structure(c(1L, 
2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 
5L, 6L, 1L), .Label = c("-3", "-2", "-1", "0", "1", "2", "3"), class = "factor"), 
    merger_it = c(0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 
    0, 1, 0, 0, 0), merger_it_pre1 = c(0, 0, 1, 0, 0, 0, 0, 0, 
    0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0), merger_it_post3 = c(0, 
    0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), 
    merger_it_post2 = c(0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 
    0, 0, 0, 0, 0, 1, 0), merger_it_post1 = c(0, 0, 0, 0, 1, 
    0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0), RD_intensity = c(7.10910850621956, 
    8.98811378416267, 15.6492601635234, 17.6773777378817, 13.1744528168514, 
    14.3544852219875, 11.2624231565094, 0.500071500320608, 0.559723756230354, 
    1.36999818636439, 1.06540748173542, NA, NA, 4.30676530109749, 
    4.28522877794115, 3.47179422075435, 3.86288780389073, 4.6469768178164, 
    NA, 26.0144516222235), age = c(36, 36, 36, 36, 36, 36, 36, 
    54, 54, 54, 54, 54, 54, 73, 73, 73, 73, 73, 73, 19), industry = c(46, 
    46, 46, 46, 46, 46, 46, 45, 45, 45, 45, 45, 45, 45, 45, 45, 
    45, 45, 45, 10), treated = c("1", "1", "1", "1", "1", "1", 
    "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", 
    "1", "1"), id = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
    2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L)), row.names = c(NA, 
-20L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x000001e028101ef0>)

Answer 1

不要在列名称周围使用引号。

library(data.table)
TandCtable[, RDexp_pre1 := c(NA, RD_expenses[-.N]), by=id]

如果你想要不同偏移长度的滞后，最好使用 @Waldi 建议的 shift 而不是附加 NA。

TandCtable[, RDexp_pre1 := shift(RD_expenses, 2), by=id]

通过 id 创建滞后变量时无法将类型 'closure' 强制转换为类型列表的向量

Cannot coerce type 'closure' to vector of type list when creating a lag variable by id

closures

r

lag

data.table