Select Input in ggplot Shiny dashboard - Error: object not found - r

I am trying to create ggplot output using R Markdown Shiny Document. I need it to plot data based on the selection in a dropdown menu. My code:
df<- data.frame(df,out)
renderRpivotTable({
rpivotTable(data = df, rows = c("organisationunitname","X2"), cols = "X1", vals = "value",
aggregatorName = "List Unique Values",inclusions = list(organisationunitname=list("All OUs")),
rendererName = "Lab Table", width = "100%", height = "500px") })
orgunit <- c("Cy3L", "Yieu", "j9ao", "H3LY", "U3nd",
"qU1l", "jXVh", "dXHb", "tCq8", "Blee", "5jra", "qO2V", "Qa9J",
"2XIy", "MJpY", "tNKa", "UorU", "7pZt", "Mxsz", "WCkd", "BiDp",
"Zw8w", "0J7c", "9YtI", "TAkB", "py3Q", "RdQt", "Yhv1", "PB0X",
"H3L4", "INY7", "DpTW", "3zXP", "OqpO", "tiZU", "5wnz")
inputPanel(selectInput("OU", label = "Select OU:", choices = orgunit, selected = "All OUs"))
renderPlot({
df1=reactive({return(df[organisationunitname %in% as.character(input$OU)])})
ggplot(data = df1(),aes(x=X1,y=value))+geom_bar(stat = "identity")+facet_grid(X2~.)
})
It gives me this error: object 'organisationunitname' not found
Error Message
My data:
structure(list(country = c("Cy3L", "Yieu", "j9ao", "H3LY", "U3nd",
"qU1l", "jXVh", "dXHb", "tCq8", "Blee", "5jra", "qO2V", "Qa9J",
"2XIy", "MJpY", "tNKa", "UorU", "7pZt", "Mxsz", "WCkd", "BiDp",
"Zw8w", "0J7c", "9YtI", "TAkB", "py3Q", "RdQt", "Yhv1", "PB0X",
"H3L4", "INY7", "DpTW", "3zXP", "OqpO", "tiZU", "5wnz"), cd4_perform_result = structure(c(24L,
6L, 7L, 1L, 1L, 1L, 5L, 3L, 2L, 1L, 10L, 1L, 2L, 8L, 1L, 2L,
17L, 1L, 1L, 23L, 12L, 1L, 14L, 11L, 18L, 1L, 21L, 16L, 1L, 22L,
19L, 4L, 1L, 15L, 20L, 9L), .Label = c("0", "1", "11", "125",
"130", "14", "15", "194", "24", "261", "27", "31", "3442", "370",
"4", "5", "51", "567", "577", "73", "76", "79", "796", "9", "end"
), class = "factor"), cd4_participate_result = c(1, 8, 8, 1,
1, 1, 5, 3, 2, 1, 7, 1, 2, 9, 1, 2, 17, 1, 1, 18, 12, 1, 4, 15,
14, 1, 20, 16, 1, 21, 10, 6, 1, 19, 13, 3), cd4_pass_result = c(1,
4, 19, 1, 1, 1, 5, 3, 2, 1, 21, 1, 2, 20, 1, 2, 13, 1, 1, 14,
6, 1, 11, 12, 10, 1, 18, 2, 1, 16, 7, 17, 1, 15, 9, 3), eid_perform_result = c(2,
1, 7, 1, 1, 1, 1, 9, 1, 1, 8, 1, 2, 3, 5, 2, 5, 1, 1, 10, 5,
1, 4, 2, 11, 1, 5, 1, 1, 5, 9, 2, 1, 1, 9, 5), eid_participate_result = c(2,
1, 5, 1, 1, 1, 1, 8, 1, 1, 7, 1, 2, 10, 5, 2, 5, 1, 1, 4, 2,
1, 10, 2, 9, 1, 5, 1, 1, 5, 7, 2, 1, 1, 6, 5), eid_pass_result = c(2,
1, 5, 1, 1, 1, 1, 7, 1, 1, 6, 1, 2, 10, 1, 2, 5, 1, 1, 4, 2,
1, 9, 2, 8, 1, 5, 1, 1, 5, 6, 2, 1, 1, 5, 5), vl_perform_result = c(2,
1, 3, 1, 1, 1, 1, 9, 1, 1, 10, 1, 2, 11, 5, 2, 5, 1, 1, 6, 5,
1, 8, 7, 6, 1, 12, 1, 1, 5, 9, 2, 1, 1, 8, 5), vl_participate_result = c(2,
1, 7, 1, 1, 1, 1, 7, 1, 1, 8, 1, 2, 8, 4, 2, 4, 1, 1, 5, 2, 1,
4, 6, 3, 1, 9, 1, 1, 4, 7, 2, 1, 1, 6, 1), vl_pass_result = c(2,
1, 7, 1, 1, 1, 1, 7, 1, 1, 9, 1, 2, 8, 1, 2, 5, 1, 1, 4, 2, 1,
2, 6, 3, 1, 11, 1, 1, 5, 7, 2, 1, 1, 5, 1), hiv_perform_result = c(19,
29, 14, 1, 1, 1, 26, 21, 10, 1, 6, 11, 9, 7, 20, 27, 8, 15, 1,
28, 12, 1, 25, 18, 24, 1, 22, 5, 1, 23, 17, 16, 1, 2, 3, 4),
hiv_participate_result = c(19, 28, 14, 1, 1, 1, 22, 20, 4,
1, 16, 9, 10, 3, 12, 27, 5, 1, 1, 21, 6, 1, 24, 18, 13, 1,
25, 8, 1, 23, 15, 17, 1, 2, 26, 7), hiv_pass_result = c(20,
28, 14, 1, 1, 1, 18, 22, 7, 1, 17, 27, 11, 2, 24, 26, 10,
1, 1, 15, 4, 1, 21, 19, 12, 1, 23, 8, 1, 16, 13, 9, 1, 3,
25, 6), tbafb_perform_result = c(9, 1, 8, 1, 1, 1, 1, 7,
1, 1, 6, 1, 21, 5, 1, 2, 12, 1, 1, 15, 13, 1, 17, 11, 20,
1, 10, 1, 1, 14, 16, 4, 1, 18, 3, 1), tbafb_participate_result = c(1,
1, 18, 1, 1, 1, 1, 5, 1, 1, 12, 1, 19, 11, 1, 2, 6, 1, 1,
13, 7, 1, 10, 9, 14, 1, 8, 1, 1, 16, 15, 4, 1, 18, 3, 1),
tbafb_pass_result = c(1, 1, 19, 1, 1, 1, 1, 6, 1, 1, 13,
1, 20, 11, 1, 2, 4, 1, 1, 15, 5, 1, 7, 10, 12, 1, 8, 1, 1,
16, 9, 3, 1, 14, 18, 1), tbculture_perform_result = c(3,
1, 2, 1, 1, 1, 1, 1, 1, 1, 6, 1, 3, 8, 1, 2, 2, 1, 1, 7,
3, 1, 5, 4, 7, 1, 5, 1, 1, 3, 6, 6, 1, 3, 3, 1), tbculture_participate_result = c(1,
1, 2, 1, 1, 1, 1, 1, 1, 1, 6, 1, 4, 9, 1, 2, 2, 1, 1, 8,
2, 1, 7, 5, 7, 1, 1, 1, 1, 4, 4, 6, 1, 4, 4, 1), tbculture_pass_result = c(1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 1, 4, 8, 1, 2, 2, 1, 1, 9,
2, 1, 7, 5, 6, 1, 1, 1, 1, 4, 4, 7, 1, 4, 4, 1), tbxpert_perform_result = c(1,
1, 4, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 17, 1, 8, 3, 1, 1, 5,
9, 1, 16, 7, 13, 1, 4, 1, 1, 12, 11, 1, 1, 6, 14, 10), tbxpert_participate_result = c(1,
1, 5, 1, 1, 1, 1, 1, 1, 1, 16, 1, 1, 4, 1, 12, 3, 1, 1, 2,
7, 1, 17, 9, 11, 1, 1, 1, 1, 14, 10, 1, 1, 6, 8, 13), tbxpert_pass_result = c(1,
1, 2, 1, 1, 1, 1, 1, 1, 1, 13, 1, 1, 4, 1, 9, 3, 1, 1, 15,
6, 1, 14, 8, 8, 1, 1, 1, 1, 12, 6, 1, 1, 5, 7, 10)), .Names = c("organisationunitname",
"cd4_perform_result", "cd4_participate_result", "cd4_pass_result",
"eid_perform_result", "eid_participate_result", "eid_pass_result",
"vl_perform_result", "vl_participate_result", "vl_pass_result",
"hiv_perform_result", "hiv_participate_result", "hiv_pass_result",
"tbafb_perform_result", "tbafb_participate_result", "tbafb_pass_result",
"tbculture_perform_result", "tbculture_participate_result", "tbculture_pass_result",
"tbxpert_perform_result", "tbxpert_participate_result", "tbxpert_pass_result"
), row.names = c(NA, 36L), class = "data.frame")
I am not sure why it's not reading the "organisationunitname" column. Please help.


I think your error is this line:
df1=reactive({return(df[organisationunitname %in% as.character(input$OU)])})
Change it to:
df1=df[df$organisationunitname %in% as.character(input$OU),])
You also have the incorrect number of dimensions and reactive is not required here because the expression is already in a reactive function: renderPlot.

Related

geom_bar(), Y-axis goes way above data value

I am trying to visualize a data frame from a survey. I'm currently trying to plot a barplot with geom_bar(), that takes in "Life Satisfaction" as the y-axis, and "Family Values" as the x-axis. Note that the survey answer for Life Satisfaction is 1(very unsatisfied) to 10(very satisfied).
But for some reason when I try to plot this barplot, the y-axis goes way above 10, and I don't understand why.
This is my code:
df1 %>%
filter(df1$B_COUNTRY_ALPHA == "PAK") %>%
drop_na(Q49) %>%
ggplot(aes(x = Q1, y = Q49, fill = B_COUNTRY_ALPHA)) +
geom_bar(stat = "identity") +
labs(x = "Family Value",
y = "Life Satisfaction")
This is the graph that I get when I run it:
This is the first 20 rows of data that I want to work with:
On a side note: I was thinking of finding the mean of the Life Satisfaction data and maybe that will make the plot make sense but I am not sure how to do that
#GregorThomas I followed your instructions and I got this.
structure(list(B_COUNTRY_ALPHA = c("PAK", "PAK", "PAK", "PAK",
"PAK", "PAK", "PAK", "PAK", "PAK", "PAK", "PAK", "PAK", "PAK",
"PAK", "PAK", "PAK", "PAK", "PAK", "PAK", "PAK"), Q49 = c(7,
10, 10, 5, 1, 6, 6, 10, 10, 10, 4, 4, 8, 10, 10, 10, 10, 9, 10,
8), Q1 = c(1, 2, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1), Q2 = c(1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1,
4, 1, 2, 2, 2), Q3 = c(2, 2, 1, 1, 3, 1, 2, 2, 2, NA, 2, 4, 1,
1, 2, 2, 4, 2, 4, 2), Q4 = c(3, 4, 2, 4, 2, 3, 4, 2, 1, 4, 4,
4, 4, 1, 3, 4, 3, 4, 4, 2), Q5 = c(1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 2, 1, 2, 1, 1, 1, 4, 1, 1, 4), Q6 = c(1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 4), Q57 = c(2, 2, 2, 1, 1,
1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, 2, 1), Q106 = c(7, 5,
10, 4, 10, 7, 1, 10, 10, 10, 1, 10, 1, 10, 10, 10, 9, 4, 10,
6), Q107 = c(7, 6, 5, 5, 10, 3, 1, 10, 10, NA, 1, 1, 1, 10, 3,
10, 10, 8, 10, 4), Q108 = c(7, 9, 1, 4, 1, 1, 10, 10, 5, 10,
10, 10, 1, 10, 10, 10, 10, 10, 1, 3), Q109 = c(6, 4, 1, 4, 1,
1, 1, 10, 10, 1, 6, 2, 10, 5, 10, 1, 10, 9, 1, 4), Q110 = c(6,
3, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5, 10, 1, 10, 3, 1, 3), Q112 =
c(8,
8, 10, 6, 10, 5, 10, 10, 10, 10, NA, 10, 10, 10, 10, 10, 10,
10, 10, 7), Q163 = c(6, 2, 10, 7, 9, 10, 10, 10, 10, NA, 10,
10, 6, 10, 3, NA, 8, 7, NA, 9), Q164 = c(4, 9, 10, 8, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, NA, 8, 10, 10, 10), Q222 = c(2,
1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 4, NA, 1, NA, 2, 3, NA, 3),
Q260 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
1, 1, 0, 1), Q262 = c(33, 21, 60, 18, 60, 50, 45, 29, 62,
46, 35, 40, 30, NA, 45, NA, 30, 50, 36, 34), Q273 = c(1,
6, 1, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
Q275 = c(0, 2, 3, 3, 3, 2, 3, 2, 4, 0, 0, 0, 1, NA, 3, NA,
1, 1, 0, 1), Q281 = c(8, 0, 3, 0, 10, 3, 4, 6, 3, 8, 4, 4,
4, 0, 5, 0, 0, 0, 9, 0)), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -20L))

Here's a couple ideas using your sample data:
Use a dodged bar plot:
sample_data %>%
ggplot(aes(x = factor(Q1), fill = factor(Q49))) +
geom_bar(position = position_dodge(preserve = 'single')) +
labs(x = "Family Value",
y = "Count of Responses",
fill = "Life Satisfaction")
Use facets:
sample_data %>%
ggplot(aes(x = factor(Q49), fill = factor(Q49))) +
geom_bar() +
labs(x = "Life Satisfaction",
y = "Count of Responses",
fill = "Life Satisfaction") +
facet_wrap(vars(paste("Family Value", Q1)))
Use a heat map:
sample_data %>%
ggplot(aes(x = factor(Q1),y = factor(Q49))) +
geom_bin2d() +
coord_fixed() +
labs(y = "Life Satisfaction", x = "Family Value")

Error using aggregate to find length with missing values

I am trying to use the aggregate function in R to summarise a data using the length function. My data has some NA's and I have tried using 'na.rm = T' or 'na.omit' however none sees to work. I keep getting this error
'Error in FUN(X[[i]], ...) :
2 arguments passed to 'length' which requires 1'
data10 <- structure(list(Group = c(1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2,
1, 2, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 2,
1), SUBJECT = c(1, 1, 2, 3, 3, 4, 5, 5, 6, 7, 8, 8, 9, 10, 10,
11, 12, 14, 14, 15, 16, 16, 17, 18, 19, 19, 20, 21, 21, 22, 23,
23, 24, 25), test = c(1, 2, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 2,
1, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 2, 2, 1
), trial = c(1, 3, 5, 7, 1, 3, 5, 7, 1, 3, 5, 7, 1, 3, 5, 7,
1, 3, 5, 7, 1, 3, 5, 7, 1, 3, 5, 7, 1, 3, 5, 7, 1, 3), Condition = c(1,
2, 3, 1, 3, 1, 2, 3, 2, 3, 1, 2, 1, 2, 3, 1, 3, 1, 2, 3, 2, 3,
1, 2, 1, 2, 3, 1, 3, 1, 2, 3, 2, 3), Sac2 = c(1, 1, 1, NA, 2,
1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 1, 1, 1, 4, 1, 1,
1, 1, 1, 1, 2, 2, 1, 1), Sac = c(1, 1, 1, NA, 3, 1, 1, 1, 1, 3,
1, 1, 1, 1, 1, 1, 1, 1, 1, 7, 1, 1, 1, 7, 1, 1, 1, 1, 1, 1, 3,
3, 1, 1), Saccade...8 = c(1, 1, 1, NA, 2, 1, 1, 1, 1, 2, 1, 1,
1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1,
1), T_APPEAR = c(9.236, 17.85, 28.942, 63.724, 9.463, 22.963,
52.068, 57.021, 15.344, 19.783, 37.825, 46.17, 4.339, 21.241,
29.179, 31.823, 12.164, 22.84, 23.954, 73.663, 27.269, 22.131,
30.361, 62.674, 6.928, 16.413, 47.555, 48.893, 7.291, 15.796,
31.788, 54.946, 10.117, 28.83)), row.names = c(NA, -34L), class = c("tbl_df",
"tbl", "data.frame"))
data14 = aggregate(data10,
by = list(data10$SUBJECT,data10$Condition, data10$Group, data10$test),
FUN = length(), na.rm=TRUE)

mixed model for paired data - 4 level outcome / 3 times

What is the correct test to evaluate the difference between 3 RX readers of the same 50 patients? The rx outcome is a categorical value with 4 ordered levels. The 3 reader have read the RX at the same time.
May I use a mixed model for paired data with patients as random effect?
I'm really in difficulty...
I've tried the repolr package for repeated ordinal scores:
repolr(formula = rsna ~ factor(reader) ,
subjects = "Patient" , data = mydata ,
categories = 4, times=c(1,2,3), po.test=TRUE,fixed=FALSE)
but I obtain this error:
Error in ord.expand(space = space, formula = formula, times = times, poly = poly, :
data: model frame and formula mismatch in model.matrix()
Here are the data:
mydata<- data.frame(Patient = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50),
reader = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3),
rsna = c(1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 4, 4, 4, 2, 1, 3, 2, 1, 1, 1, 2, 1, 3, 1, 1, 1, 3, 1, 1, 1, 1, 1, 4, 2, 2, 1, 1))
rsna is my outcome with 4 levels, Patients are the 50 patients, reader are the 3 readers.
How can I fix it?

If you turn the reader variable into a factor in the dataset first, it works:
mydata<- data.frame(Patient = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50),
reader = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3),
rsna = c(1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 4, 4, 4, 2, 1, 3, 2, 1, 1, 1, 2, 1, 3, 1, 1, 1, 3, 1, 1, 1, 1, 1, 4, 2, 2, 1, 1))
mydata$reader <- as.factor(mydata$reader)
library(repolr)
repolr(formula = rsna ~ reader,
subjects = "Patient" , data = mydata ,
categories = 4, times=c(1,2,3), po.test=TRUE,fixed=FALSE)
#>
#> repolr: 2016-02-26 version 3.4
#>
#> Call:
#> repolr(formula = rsna ~ reader, subjects = "Patient", data = mydata,
#> times = c(1, 2, 3), categories = 4, po.test = TRUE, fixed = FALSE)
#>
#> Coefficients:
#> cuts1|2 cuts2|3 cuts3|4 reader2 reader3
#> 1.1761 2.1395 2.9071 0.6600 -0.4768
Created on 2022-06-07 by the reprex package (v2.0.1)

Bootstrapping multiple regression error: number of items to replace is not a multiple of replacement length

I want to bootstrap my dataset for multiple regression. Unfortunately I get this error message:
"number of items to replace is not a multiple of replacement length"
I suspect that the factors in my regression formula may be problematic.
What could I do to solve my problem?
My code is as following (I read Andy Field´s Discovering Statistics using R):
BootReg <- function(data, indices, formula) {
d <- data[indices,]
fit <- lm(formula, data=d)
return(coef(fit))
}
bootResults <-boot(statistic = BootReg, formula = TICS_Skala1 ~HSPhoch + HSPhoch*extra.c
+ psy + sex + age.c, data = mod.reg.data, R = 2000)
psy (psychiatric disease), sex and HSPhoch (high sensory-processing sensitivity) are factors. TICS_Skala1, extra.c, age.c are continuos variables.
my sample data:
> dput(head(mod.reg.data, 20))
structure(list(neo_01 = c(3, 4, 3, 0, 4, 4, 3, 2, 3, 1, 4, 2,
3, 3, 1, 2, 3, 4, 0, 2), neo_03 = c(1, 1, 1, 3, 1, 2, 0, 0, 0,
0, 0, 0, 1, 3, 1, 1, 1, 1, 3, 1), neo_04 = c(2, 4, 3, 0, 4, 3,
4, 3, 2, 3, 3, 3, 3, 4, 2, 4, 3, 4, 3, 3), neo_08 = c(3, 0, 1,
2, 3, 3, 4, 3, 2, 1, 2, 4, 0, 3, 1, 1, 3, 1, 3, 1), neo_12 = c(3,
1, 1, 2, 2, 2, 4, 1, 1, 2, 1, 4, 1, 3, 1, 1, 3, 2, 3, 2), neo_13 = c(3,
2, 2, 4, 3, 3, 3, 2, 2, 1, 2, 3, 0, 3, 1, 0, 2, 3, 0, 2), neo_16 = c(3,
1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 3, 0, 2, 0, 0, 0, 0, 2, 1), neo_17 = c(2,
1, 3, 0, 1, 1, 1, 4, 3, 1, 2, 2, 2, 3, 1, 0, 2, 0, 2, 2), neo_18 = c(2,
3, 4, 0, 4, 3, 4, 3, 3, 1, 3, 2, 4, 2, 3, 4, 3, 4, 2, 2), neo_21 = c(3,
0, 1, 2, 1, 2, 1, 1, 1, 1, 1, 3, 0, 4, 1, 0, 0, 0, 4, 1), neo_26 = c(3,
0, 0, 0, 2, 1, 3, 0, 1, 1, 0, 2, 3, 3, 0, 0, 1, 1, 4, 1), neo_27 = c(3,
3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 4, 3, 3, 3, 3, 2, 2), TICS_1 = c(3,
0, 3, 2, 2, 1, 3, 3, 1, 2, 0, 4, 2, 3, 2, 3, 4, 1, 3, 2), TICS_2 = c(3,
1, 1, 1, 1, 2, 0, 0, 0, 0, 0, 4, 3, 1, 1, 1, 2, 1, 2, 1), TICS_3 = c(2,
1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 3, 1, 2, 0, 1, 1, 0, 1, 0), TICS_4 = c(2,
0, 2, 0, 1, 2, 1, 3, 0, 0, 0, 4, 1, 2, 1, 2, 1, 1, 2, 2), TICS_5 = c(2,
3, 2, 1, 2, 2, 2, 2, 0, 2, 1, 2, 2, 2, 2, 1, 1, 1, 2, 1), TICS_6 = c(3,
2, 2, 4, 2, 2, 1, 3, 1, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 2), TICS_7 = c(3,
3, 2, 2, 2, 2, 0, 3, 1, 2, 1, 4, 2, 0, 2, 1, 4, 1, 0, 1), TICS_8 =c(NA,
NA, NA, NA, NA, NA, NA, NA, 1, 1, 0, 4, 3, 1, 1, 3, 3, 2, 1,
2), TICS_9 = c(NA, NA, NA, NA, NA, NA, NA, NA, 0, 3, 2, 2, 1,
3, 0, 1, 3, 1, 1, 2), TICS_10 = c(2, 2, 0, 0, 2, 3, 0, 2, 1,
1, 2, 2, 1, 0, 0, 1, 1, 2, 2, 1), TICS_11 = c(1, 2, 1, 0, 1,
1, 0, 0, 0, 0, 2, 4, 1, 0, 0, 0, 0, 1, 1, 0), TICS_12 = c(2,
2, 1, 0, 1, 1, 1, 3, 1, 1, 1, 4, 2, 2, 2, 3, 3, 1, 2, 3), TICS_13=
c(1, 1, 3, 0, 2, 3, 2, 1, 1, 2, 1, 2, 2, 3, 2, 2, 1, 2, 2, 2),
TICS_14= c(4, 1, 1, 0, 1, 1, 3, 4, 0, 2, 0, 4, 2, 3, 0, 1, 3, 1, 1,
1), TICS_15= c(3, 1, 1, 3, 0, 2, 0, 2, 0, 2, 1, 2, 0, 1, 1, 1, 0, 0,
0, 1), ICS_16= c(4, 2, 1, 3, 3, 2, 1, 2, 1, 1, 1, 3, 1, 3, 1, 2, 3,
1, 2, 1), TICS_17= c(3, 0, 2, 2, 1, 2, 2, 3, 0, 1, 1, 2, 1, 2, 2, 3,
1, 1, 1, 2), TICS_18= c(3, 0, 1, 2, 0, 1, 1, 0, 0, 1, 0, 4, 2, 2, 0,
0, 1, 0, 2, 0), TICS_19= c(4, 2, 2, 2, 2, 2, 0, 2, 1, 2, 1, 4, 3, 2,
1, 1, 1, 0, 1, 2), TICS_20= c(2, 0, 2, 0, 0, 0, 1, 0, 1, 1, 0, 4, 1,
1, 0, 0, 1, 0, 2, 0), TICS_21= c(2, 1, 1, 0, 2, 3, 0, 1, 0, 1, 3, 2,
2, 1, 2, 1, 1, 1, 3, 0), TICS_22= c(3, 0, 1, 2, 2, 3, 1, 4, 0, 1, 1,
2, 3, 1, 1, 2, 3, 2, 0, 3), TICS_24= c(2, 0, 0, 1, 0, 0, 2, 0, 1, 1,
0, 2, 0, 0, 0, 1, 1, 0, 0, 1), TICS_25= c(4, 0, 1, 2, 2, 2, 4, 2, 1,
1, 0, 3, 0, 2, 0, 1, 2, 1, 2, 1), TICS_26= c(3, 0, 2, 2, 0, 1, 1, 0,
0, 1, 0, 2, 0, 2, 0, 0, 0, 0, 0, 1), TICS_27= c(3,
1, 4, 2, 3, 3, 4, 4, 0, 1, 0, 3, 2, 3, 2, 3, 2, 2, 4, 3), TICS_28=
c(3, 2, 2, 1, 1, 2, 1, 2, 1, 1, 0, 4, 1, 2, 1, 0, 1, 0, 0, 2),
TICS_29= c(2, 0, 1, 0, 2, 2, 1, 0, 1, 0, 0, 4, 1, 1, 0, 1, 0, 0, 1,
1), TICS_30= c(2, 1, 3, 1, 2, 2, 1, 0, 1, 1, 1, 3, 2, 0, 1, 0, 1, 2,
2, 2), TICS_31= c(2, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 3, 2, 1, 0, 0, 1,
0, 2, 1), TICS_32= c(4, 1, 1, 0, 1, 2, 1, 4, 0, 3, 0, 3, 3, 2, 1, 2,
2, 2, 3, 3), TICS_33= c(2,
1, 0, 2, 1, 1, 1, 1, 0, 0, 0, 1, 0, 2, 0, 0, 0, 1, 1, 1), TICS_34=
c(1, 3, 0, 0, 2, 1, 1, 1, 0, 0, 2, 4, 0, 0, 0, 0, 0, 0, 0, 0),
TICS_35= c(1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 2, 0, 1, 0, 1, 1, 0, 4,
1), TICS_36= c(4, 1, 2, 3, 3, 2, 4, 1, 0, 1, 2, 3, 1, 3, 0, 1, 1, 0,
2, 1), TICS_37= c(1, 1, 2, 0, 2, 3, 3, 0, 1, 2, 1, 2, 1, 0, 2, 2, 1,
1, 2, 1), TICS_38= c(3, 0, 3, 1, 2, 2, 2, 3, 0, 2, 0, 4, 0, 2, 1, 2,
2, 1, 1, 2), TICS_39= c(1, 1, 2, 2, 3, 1, 1, 2, 1, 1, 1, 4, 1, 1, 1,
1, 3, 0, 0, 3), TICS_40= c(2, 0, 2, 0, 3, 2, 1, 2, 0, 0, 0, 3, 2, 2,
0, 1, 2, 0, 0, 1), TICS_41= c(2, 2, 0, 0, 2, 3, 1, 1, 0, 1, 3, 1, 2,
0, 1, 0, 0, 1, 2, 0), TICS_42= c(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 2,
1, 1, 1, 0, 0, 0, 0, 0), TICS_43= c(4,
1, 1, 2, 2, 3, 3, 3, 0, 2, 1, 4, 3, 2, 1, 1, 3, 1, 2, 3), TICS_44=
c(3, 0, 2, 1, 2, 2, 3, 3, 0, 1, 0, 4, 1, 3, 0, 2, 2, 1, 3, 1),
TICS_45= c(2,
0, 1, 2, 0, 1, 0, 2, 0, 1, 0, 2, 0, 2, 0, 0, 0, 0, 0, 1), TICS_46=
c(2, 1, 0, 1, 2, 2, 1, 0, 0, 3, 1, 4, 3, 1, 1, 0, 1, 1, 2, 1),
TICS_47= c(3,
1, 2, 1, 2, 2, 1, 1, 1, 2, 0, 3, 1, 2, 1, 2, 1, 1, 4, 1), TICS_48=
c(1,
2, 3, 1, 2, 3, 1, 1, 0, 2, 2, 4, 2, 3, 2, 2, 1, 0, 2, 0), TICS_49=
c(1,
3, 2, 2, 1, 2, 2, 1, 0, 1, 1, 4, 3, 0, 1, 2, 4, 1, 0, 3), TICS_50=
c(3,
0, 3, 1, 1, 2, 4, 3, 0, 2, 0, 4, 2, 3, 2, 2, 2, 2, 2, 3), TICS_51=
c(1,
2, 0, 0, 2, 1, 0, 0, 0, 0, 1, 2, 1, 0, 1, 0, 0, 0, 0, 0), TICS_52=
c(2,
1, 3, 0, 1, 1, 1, 1, 0, 1, 0, 2, 0, 3, 0, 0, 0, 0, 0, 1), TICS_53=
c(2,
2, 2, 0, 2, 3, 1, 1, 0, 2, 2, 3, 2, 2, 2, 1, 1, 1, 2, 1), TICS_54=
c(3,
0, 3, 2, 2, 2, 3, 3, 1, 2, 0, 4, 0, 2, 0, 2, 2, 0, 2, 1), TICS_55=
c(2,
0, 0, 1, 0, 1, 2, 0, 0, 1, 0, 4, 0, 1, 0, 1, 1, 0, 2, 0), TICS_56=
c(4,
3, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 1, 1, 0, 0, 0, 2, 0), TICS_57=
c(2,
1, 1, 0, 2, 1, 0, 0, 1, 1, 1, 4, 3, 0, 0, 1, 1, 0, 0, 2), HSPS_1 =
c(3,
4, 3, 3, 4, 2, 4, 2, 4, 2, 3, 4, 2, 2, 4, 2, 3, 3, 5, 2), HSPS_2 =
c(4,
4, 3, 5, 5, 3, 2, 4, 5, 5, 3, 4, 3, 4, 4, 2, 4, 3, 4, 3), HSPS_3 =
c(4,
4, 4, 3, 3, 4, 3, 3, 3, 3, 3, 5, 3, 4, 5, 3, 3, 3, 4, 2), HSPS_4 =
c(4,
2, 1, 4, 2, 3, 5, 3, 5, 2, 3, 3, 3, 4, 3, 3, 4, 2, 5, 2), HSPS_5 =
c(2,
2, 2, 4, 3, 3, 3, 1, 4, 3, 3, 4, 3, 2, 4, 3, 4, 3, 5, 1), HSPS_6 =
c(4,
3, 1, 3, 4, 3, 3, 3, 3, 2, 1, 1, 1, 3, 5, 3, 3, 1, 1, 2), HSPS_7 =
c(4,
3, 1, 3, 4, 2, 3, 1, 4, 3, 2, 4, 1, 1, 5, 3, 3, 1, 5, 1), HSPS_8 =
c(4,
3, 5, 5, 4, 5, 5, 3, 4, 4, 3, 3, 2, 4, 4, 3, 4, 3, 3, 3), HSPS_9 =
c(3,
2, 2, 5, 3, 3, 4, 1, 5, 2, 2, 4, 1, 2, 4, 4, 3, 1, 5, 2), HSPS_10=
c(4,
4, 5, 4, 4, 4, 3, 1, 4, 3, 3, 4, 2, 1, 5, 3, 4, 4, 3, 2), HSPS_11=
c(3,
2, 2, 3, 2, 2, 3, 1, 3, 2, 4, 5, 1, 3, 3, 3, 3, 2, 3, 2), HSPS_12=
c(4,
4, 5, 5, 4, 5, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 4, 4, 5, 4), HSPS_13=
c(3,
2, 3, 2, 2, 2, 5, 2, 3, 2, 3, 4, 3, 3, 3, 3, 4, 2, 5, 2), HSPS_14=
c(3,
2, 2, 3, 3, 3, 5, 3, 3, 2, 3, 3, 2, 3, 2, 3, 3, 2, 4, 2), HSPS_15=
c(4,
4, 2, 3, 4, 3, 3, 3, 4, 2, 3, 3, 5, 2, 4, 2, 3, 3, 3, 2), HSPS_16=
c(2,
2, 1, 5, 2, 3, 2, 2, 3, 3, 3, 5, 2, 3, 3, 3, 2, 2, 5, 2), HSPS_17=
c(4,
3, 4, 5, 3, 4, 4, 2, 4, 3, 5, 4, 4, 4, 5, 4, 5, 2, 5, 4), HSPS_18=
c(2,
2, 1, 2, 1, 2, 2, 1, 3, 2, 2, 5, 2, 1, 4, 3, 2, 1, 5, 1), HSPS_19=
c(3,
2, 2, 4, 2, 2, 3, 1, 4, 2, 2, 4, 1, 1, 4, 3, 2, 2, 5, 2), HSPS_20=
c(4,
4, 4, 3, 4, 3, 5, 3, 3, 3, 4, 3, 3, 4, 4, 3, 5, 3, 5, 2), HSPS_21=
c(3,
3, 4, 5, 3, 3, 5, 2, 4, 2, 3, 5, 4, 4, 3, 2, 3, 2, 5, 2), HSPS_22=
c(3,
5, 5, 4, 5, 4, 3, 2, 4, 3, 3, 5, 3, 2, 4, 2, 4, 3, 5, 2), HSPS_23=
c(2,
2, 1, 4, 2, 3, 4, 3, 3, 2, 2, 5, 3, 3, 3, 3, 3, 2, 5, 3), HSPS_24=
c(3,
2, 2, 3, 3, 3, 3, 2, 4, 2, 3, 5, 4, 2, 4, 4, 4, 3, 4, 2), HSPS_25=
c(3,
2, 2, 5, 3, 3, 5, 1, 4, 2, 3, 5, 3, 2, 4, 3, 3, 2, 5, 2), HSPS_26=
c(2,
1, 1, 3, 3, 3, 3, 2, 3, 2, 2, 5, 2, 2, 3, 3, 3, 2, 5, 2), HSPS_27=
c(2,
2, 1, 4, 3, 2, 3, 4, 3, 1, 4, 1, 1, 3, 4, 2, 3, 2, 5, 3), sex =
structure(c(2L,
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L), .Label = c("m", "w", "d"), class = "factor"), Bildung =
structure(c(6L,
5L, 5L, 6L, 6L, 6L, 5L, 6L, 5L, 6L, 6L, 4L, 6L, 5L, 5L, 6L, 6L,
5L, 5L, 6L), .Label = c("kein", "Haupt", "mittlereR", "Fachabi",
"Abi", "Studium"), class = "factor"), job = structure(c(6L, 2L,
2L, 2L, 2L, 6L, 2L, 6L, 5L, 2L, 2L, 1L, 6L, 2L, 2L, 2L, 6L, 2L,
2L, 6L), .Label = c("hausl", "Student", "Azubi", "Suchend", "Rente",
"berufstaetig"), class = "factor"), age = c(23, 24, 21, 70, 25,
29, 22, 25, 57, 24, 25, 30, 31, 20, 28, 27, 26, 21, 24, 53),
VPN = 1:20, consent = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label =
c("ja",
"nein"), class = "factor"), psy = c(0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0), HSPS = c(86, 75,
69, 102, 85, 82, 97, 59, 100, 68, 80, 106, 68, 73, 105, 79,
91, 63, 119, 59), neuro = c(16, 3, 4, 10, 10, 11, 12, 5,
5, 5, 5, 16, 5, 18, 4, 3, 8, 5, 19, 7), extra = c(15, 17,
19, 7, 19, 17, 18, 17, 16, 10, 17, 14, 15, 19, 11, 13, 16,
18, 9, 13), TICS_Skala1 = c(23, 1, 22, 11, 14, 16, 22, 25,
2, 11, 1, 29, 9, 20, 10, 19, 16, 9, 18, 16), TICS_Skala2 = c(14,
12, 11, 9, 11, 10, 4, 10, 5, 8, 5, 24, 13, 5, 6, 6, 14, 2,
1, 13), TICS_Skala3 = c(21, 6, 10, 5, 12, 14, 11, 20, 3,
11, 4, 27, 20, 13, 7, 13, 20, 11, 11, 18), TICS_Skala4 = c(13,
14, 13, 2, 16, 23, 10, 9, 3, 13, 15, 18, 14, 11, 13, 10,
7, 9, 17, 6), TICS_Skala5 = c(12, 2, 6, 5, 3, 5, 8, 3, 4,
6, 0, 18, 3, 7, 1, 6, 6, 1, 13, 3), TICS_Skala6 = c(10, 2,
3, 4, 4, 6, 3, 0, 0, 5, 2, 15, 10, 5, 2, 1, 5, 2, 8, 3),
TICS_Skala7 = c(15, 5, 9, 13, 4, 8, 4, 9, 1, 6, 2, 11, 2,
12, 3, 2, 1, 3, 2, 7), TICS_Skala8 = c(8, 10, 3, 0, 11, 7,
2, 1, 2, 2, 7, 20, 7, 2, 2, 2, 1, 1, 2, 3), TICS_Skala9 = c(12,
3, 4, 8, 8, 6, 9, 5, 2, 6, 5, 11, 3, 11, 1, 5, 9, 3, 7, 5
), TICS_Skala10 = c(32, 5, 18, 16, 19, 18, 21, 16, 5, 17,
7, 39, 12, 24, 3, 15, 20, 6, 25, 14), neuro.c = c(6.08921933085502,
-6.91078066914498, -5.91078066914498, 0.089219330855018,
0.089219330855018, 1.08921933085502, 2.08921933085502,
-4.91078066914498,
-4.91078066914498, -4.91078066914498, -4.91078066914498,
6.08921933085502, -4.91078066914498, 8.08921933085502,
-5.91078066914498,
-6.91078066914498, -1.91078066914498, -4.91078066914498,
9.08921933085502, -2.91078066914498), extra.c = c(5.21003717472119,
7.21003717472119, 9.21003717472119, -2.78996282527881,
9.21003717472119,
7.21003717472119, 8.21003717472119, 7.21003717472119,
6.21003717472119,
0.21003717472119, 7.21003717472119, 4.21003717472119,
5.21003717472119,
9.21003717472119, 1.21003717472119, 3.21003717472119,
6.21003717472119,
8.21003717472119, -0.78996282527881, 3.21003717472119), age.c =
c(-15.4460966542751,
-14.4460966542751, -17.4460966542751, 31.5539033457249,
-13.4460966542751,
-9.4460966542751, -16.4460966542751, -13.4460966542751,
18.5539033457249,
-14.4460966542751, -13.4460966542751, -8.4460966542751,
-7.4460966542751,
-18.4460966542751, -10.4460966542751, -11.4460966542751,
-12.4460966542751, -17.4460966542751, -14.4460966542751,
14.5539033457249), HSP.c = c(-1.92936802973978, -12.9293680297398,
-18.9293680297398, 14.0706319702602, -2.92936802973978,
-5.92936802973978,
9.07063197026022, -28.9293680297398, 12.0706319702602,
-19.9293680297398,
-7.92936802973978, 18.0706319702602, -19.9293680297398,
-14.9293680297398,
17.0706319702602, -8.92936802973978, 3.07063197026022,
-24.9293680297398,
31.0706319702602, -28.9293680297398), HSPhoch = c(1, 0, 0,
1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0)), row.names =
c(NA, 20L), class = "data.frame")

How to fix invalid vertex id error in tidygraph?

Data
network_data <- list(nodes = structure(list(id = c(0, 1, 2, 3, 4, 5, 6, 7, 8,
9, 10, 11, 12, 13, 14), label = c("2892056", "2894543", "2894544",
"2894545", "2894546", "2894547", "2894548", "2894549", "2894550",
"2894551", "2894552", "2894553", "2894554", "2894555", "2894556"
)), row.names = c(NA, -15L), class = "data.frame"), links = structure(list(
from = c(3, 5, 7, 13, 13, 7, 3, 5, 0, 0, 5, 2, 7, 6, 13,
11, 0, 3, 2, 7, 13, 3, 0, 0, 5, 3, 13, 4, 0, 14, 13, 7, 2,
3, 5, 0, 12), to = c(0, 0, 0, 0, 2, 2, 2, 2, 2, 3, 3, 3,
3, 3, 3, 4, 5, 5, 5, 5, 5, 6, 6, 7, 7, 7, 7, 11, 12, 12,
12, 13, 13, 13, 13, 13, 14), weight = c(1, 2, 2, 1, 2, 1,
1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 1, 1,
2, 1, 2, 1, 1, 2, 2, 2, 1, 2, 1, 1)), row.names = c(NA, -37L
), class = "data.frame"))
I have this list of nodes and links for building a network. Rather than plotting the network, I want to get the network characteristics such as isolates, reciprocity, etc.
Here's the rest of the code that I'm using to obtain these characteristics:
network_data$nodes <- network_data$nodes %>% select(id, label)
network_data$links <- network_data$links %>% rename(from = source, to = target)
print(network_data$nodes)
print(network_data$links)
SNA <- tidygraph::tbl_graph(
nodes = network_data$nodes,
edges = network_data$links,
directed = T
)
The last line is where it errors out.
Error in (function (edges, n = max(edges), directed = TRUE) :
At structure_generators.c:86 : Invalid (negative) vertex id, Invalid vertex id
I googled the issue and seems like it's pretty prevalent, but none of the methods suggested worked for me. What's different in my data that it's still generating the error, and how can I resolve this error?

Resources