In caseybreen/wcensoc:
[^updated]: Last updated: r format(Sys.time(), '%d %B, %Y')
| Page| Variable | Label |
|----:|:------------------------|:---------------------------------------------|
| \hyperlink{page.2}{2} | \hyperlink{page.2}{HISTID} |Historical unique identifier |
| \hyperlink{page.3}{3} | \hyperlink{page.3}{byear} |Year of birth |
| \hyperlink{page.4}{4} | \hyperlink{page.4}{bmonth} |Month of birth |
| \hyperlink{page.5}{5} | \hyperlink{page.5}{dyear} |Year of death |
| \hyperlink{page.6}{6} | \hyperlink{page.6}{dmonth} |Month of death |
| \hyperlink{page.7}{7} | \hyperlink{page.7}{death_age} |Age at death (years) |
| \hyperlink{page.8}{8} | \hyperlink{page.8}{link_abe_exact_conservative} |Flag for conservative ABE match |
| \hyperlink{page.9}{9} | \hyperlink{page.9}{weight} |CenSoc weight |
| \hyperlink{page.10}{10} | \hyperlink{page.10}{weight_conservative} |CenSoc weight (Conservative Sample) |
| \hyperlink{page.11}{11} | \hyperlink{page.11}{pernum} |Person number in sample weight|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{perwt} |IPUMS person weight|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{age} |Age in 1940|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{sex} |Sex in 1940|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{bpl} |Place of birth|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{mbpl} |Mother's place of birth|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{fbpl} |Father's place of birth|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{educd} |Educational attainment (detailed)|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{educ_yrs} |Educational attainment in years (constructed)|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{empstatd} |Employment status (detailed)|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{hispan} |Hispanic/Spanish/Latino origin|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{inconwg} |Had non-wage/salary income over $50|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{marst} |Marital status|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{nativity} |Foreign birthplace or parentage|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{occ} |Occupation|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{occscore} |Occupational income score|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{ownership} |Ownership of dwelling (tenure)|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{race} |Race|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{rent} |Montly contract rent|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{serial} |Household serial number|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{statefip} |State of residence 1940|
| \hyperlink{page.11}{11} | \hyperlink{page.11}{urban} |Urban/rural status|
\vspace{50pt}
Summary: The CenSoc-DMF Version 2.1 Demo dataset (N = 70,211) links the IPUMS 1940 1% census sample to the Death Master File (DMF) dataset, a collection of death records reported to the Social Security Administration. Records were linked using the standard and conservative ABE method developed by Abramitzky, Boustan, and Eriksson (2012, 2014, 2017). Note, the demo file isn’t conducive to high-resolution mortality research, and we recommend researchers obtain a copy of the 1940 Census from IPUMS-USA and link on the individual-level, unique identifier HISTID variable.
\newpage
\huge HISTID
\normalsize
\vspace{12pt}
Label: Historical Unique Identifier
Description: HISTID is a unique individual-level identifier. It can be used to merge the CenSoc-DMF file with the 1940 Full-Count Census from IPUMS.
\newpage
\huge byear
\normalsize
\vspace{12pt}
Label: Birth Year
Description: byear reports a person's year of birth, as recorded in the Social Security Death Master File.
## Library Packages
library(tidyverse)
library(data.table)
## read in censoc_dmf_v2.1 data file
censoc_dmf_v2.1<-read_csv("/data/censoc/censoc_data_releases/censoc_dmf_demo/censoc_dmf_demo_v2.1/censoc_dmf_demo_v2.1.csv")
byear_plot <- censoc_dmf_v2.1 %>%
group_by(byear) %>%
summarise(n = n()) %>%
ggplot(aes(x = byear, y = n)) +
geom_line() +
geom_point() +
theme_minimal(base_size = 15) + #replace with a different theme (theme_bw()) if the bbplot package isn't downloaded
ggtitle("Year of Birth") +
theme(legend.position="bottom") +
xlab("title") +
labs(x = "Year",
y = "Count") +
scale_y_continuous(labels = scales::comma) +
scale_x_continuous(breaks = scales::pretty_breaks(n=5))
\vspace{75pt}
byear_plot
\newpage
\huge bmonth
\normalsize
\vspace{12pt}
Label: Birth Month
Description: bmonth reports a person's month of birth, as recorded in the Social Security Death Master File.
## run in the console and copy and paste into documentation
bmonth_tabulated <- knitr::kable(censoc_dmf_v2.1 %>%
filter(bmonth != 0) %>%
group_by(bmonth) %>%
tally() %>%
mutate(freq = signif(n*100 / sum(n), 2)) %>%
mutate(label = c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December")) %>%
select(bmonth, label, n, `freq %` = freq))
\vspace{30pt}
bmonth_tabulated
\newpage
\huge dyear
\normalsize
\vspace{12pt}
Label: Death Year
Description: dyear reports a person's year of death, as recorded in the Social Security Death Master File.
dyear_plot <-
censoc_dmf_v2.1 %>%
group_by(dyear) %>%
summarise(n = n()) %>%
ggplot(aes(x = dyear, y = n)) +
geom_line() +
geom_point() +
theme_minimal(base_size = 15) +
ggtitle("Year of Death") +
theme(legend.position="bottom") +
xlab("title") +
labs(x = "Year",
y = "Count") +
scale_y_continuous(labels = scales::comma, limits = c(0, 3000)) +
scale_x_continuous(breaks = scales::pretty_breaks(n=5))
\vspace{75pt}
dyear_plot
\newpage
\huge dmonth
\normalsize
\vspace{12pt}
Label: Death Month
Description: dmonth reports a person's month of death, as recorded in the Social Security Death Master File.
dmonth_tabulated <- knitr::kable(censoc_dmf_v2.1 %>%
group_by(dmonth) %>%
tally() %>%
mutate(freq = signif(n*100 / sum(n), 2)) %>%
mutate(label = c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December")) %>%
select(dmonth, label, n, `freq %` = freq))
\vspace{30pt}
dmonth_tabulated
\newpage
\huge death_age
\normalsize
\vspace{12pt}
Label: Age at Death (Years)
Description: death_age reports a person's age at death in years, calculated using the birth and death information recorded in the Social Security Death Master File.
death_age_plot <- censoc_dmf_v2.1 %>%
group_by(death_age) %>%
summarise(n = n()) %>%
ggplot(aes(x = death_age, y = n)) +
geom_line() +
geom_point() +
theme_minimal(base_size = 15) + #replace with a different theme (theme_bw()) if the bbplot package isn't downloaded
ggtitle("Age at Death") +
theme(legend.position="bottom") +
xlab("title") +
labs(x = "Age at Death",
y = "Count") +
scale_y_continuous(labels = scales::comma) +
scale_x_continuous(breaks = scales::pretty_breaks(n=5))
\vspace{75pt}
death_age_plot
\newpage
\huge link_abe_exact_conservative
\normalsize
\vspace{12pt}
Label: Flag for conservative ABE match
Description: A flag variable reporting whether a match was established with the ABE conservative match with exact names.
link_abe_exact_conservative_tabulated <- knitr::kable(censoc_dmf_v2.1 %>%
group_by(link_abe_exact_conservative) %>%
tally() %>%
mutate(freq = signif(n*100 / sum(n), 3)) %>%
arrange(desc(link_abe_exact_conservative)) %>%
mutate(label = c("Conservative and Standard ABE Link", "Standard ABE Link Only")) %>%
select(link_abe_exact_conservative, label, n, `freq %` = freq))
\vspace{50pt}
link_abe_exact_conservative_tabulated
\newpage
\huge weight
\normalsize
\vspace{12pt}
Label: Sample Weights[^1]
Description: A post-stratification person-weight to Human Mortality Database (HMD) totals for persons (1) born between 1895-1939 (2) dying between 1975-2005 (3) dying between ages 65-100. Please see the CenSoc Methods Protocol for more details on weighting procedure.
[^1]: The IPUMS-USA 1940 1% sample also includes a weight (perweight) to account for the 1940 sampling procedure (thus no weights for the 100% complete count 1940 census). For analysis, we recommend using both sets of weights. A final weight can be constructed by multiplying the two weights together.
weights_tabulated <- censoc_dmf_v2.1 %>%
filter(!is.na(weight)) %>%
summarize('Min Weight' = round(min(weight),2), 'Max Weight' = round(max(weight), 2)) %>%
mutate(id = 1:n()) %>%
pivot_longer(-id, names_to = "Label", values_to = "Value") %>%
select(Value, Label) %>%
add_row(Label = "No Weight Assigned", Value = NA) %>%
knitr::kable()
weight.plot <- censoc_dmf_v2.1 %>%
filter(!is.na(weight)) %>%
ggplot() +
geom_boxplot(aes(x=weight), fill='grey92') +
ylim(-1,1) +
theme_minimal(15) +
theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
ggtitle("Distribution of Weights") +
xlab('Weight')
\vspace{50pt}
weights_tabulated
\vspace{50pt}
weight.plot
\newpage
\huge weight_conservative
\normalsize
\vspace{12pt}
Label: Sample Weights (Conservative Sample)
Description: A post-stratification person-weight to Human Mortality Database (HMD) totals (only for matches established via the conservative ABE algorithm) for persons (1) born between 1895-1939 (2) dying between 1975-2005 (3) dying between ages 65-100. Please see the CenSoc Methods Protocol for more details on weighting procedure.
weights_conservtive_tabulated <- censoc_dmf_v2.1 %>%
filter(link_abe_exact_conservative == 1) %>%
filter(!is.na(weight_conservative)) %>%
summarize('Min Weight' = round(min(weight_conservative),2), 'Max Weight' = round(max(weight_conservative), 2)) %>%
mutate(id = 1:n()) %>%
pivot_longer(-id, names_to = "Label", values_to = "Value") %>%
select(Value, Label) %>%
add_row(Label = "No Weight Assigned", Value = NA) %>%
knitr::kable()
weight_conservative.plot <- censoc_dmf_v2.1 %>%
filter(link_abe_exact_conservative == 1) %>%
filter(!is.na(weight_conservative)) %>%
ggplot() +
geom_boxplot(aes(x=weight_conservative), fill='grey92') +
ylim(-1,1) +
theme_minimal(15) +
theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
ggtitle("Distribution of Weights") +
xlab('Weight')
\vspace{50pt}
weights_conservtive_tabulated
\vspace{50pt}
weight_conservative.plot
\newpage
\huge IPUMS 1940 Census Variable
\normalsize
\vspace{12pt}
The variables below are from the IPUMS-USA 1940 1% census sample. We recommend looking at the terrific documentation on the IPUMS-USA website: \hyperlink{https://usa.ipums.org/usa/index.shtml}{https://usa.ipums.org/usa/index.shtml.}
| Variable | Label |
|:-------------|:---------------------------------------------|
| pernum |Person number in sample weight|
|perwt |IPUMS person weight[^2] |
| age |Age in 1940|
| sex |Sex in 1940|
| bpl |Place of birth|
| mbpl |Mother's place of birth|
| fbpl |Father's place of birth|
| educd |Educational attainment (detailed)|
| educ_yrs |Educational attainment in years (constructed)|
| empstatd |Employment status (detailed)|
| hispan |Hispanic/Spanish/Latino origin|
| inconwg |Had non-wage/salary income over $50|
| marst |Marital status|
| nativity |Foreign birthplace or parentage|
| occ |Occupation|
| occscore |Occupational income score|
| ownership |Ownership of dwelling (tenure)|
| race |Race|
| rent |Montly contract rent|
| serial |Household serial number|
| statefip |State of residence 1940|
| urban |Urban/rural status|
[^2]: The perweight accounts for the 1940 sampling procedure to construct the 1% sample, and thus is only available in the 1940 1% sample. For analysis, we recommend using both the IPUMS perweight and the CenSoc weight. A final weight can be constructed by multiplying the two weights together
caseybreen/wcensoc documentation built on Nov. 21, 2024, 5:15 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
[^updated]: Last updated: r format(Sys.time(), '%d %B, %Y')
| Page| Variable | Label | |----:|:------------------------|:---------------------------------------------| | \hyperlink{page.2}{2} | \hyperlink{page.2}{HISTID} |Historical unique identifier | | \hyperlink{page.3}{3} | \hyperlink{page.3}{byear} |Year of birth | | \hyperlink{page.4}{4} | \hyperlink{page.4}{bmonth} |Month of birth | | \hyperlink{page.5}{5} | \hyperlink{page.5}{dyear} |Year of death | | \hyperlink{page.6}{6} | \hyperlink{page.6}{dmonth} |Month of death | | \hyperlink{page.7}{7} | \hyperlink{page.7}{death_age} |Age at death (years) | | \hyperlink{page.8}{8} | \hyperlink{page.8}{link_abe_exact_conservative} |Flag for conservative ABE match | | \hyperlink{page.9}{9} | \hyperlink{page.9}{weight} |CenSoc weight | | \hyperlink{page.10}{10} | \hyperlink{page.10}{weight_conservative} |CenSoc weight (Conservative Sample) | | \hyperlink{page.11}{11} | \hyperlink{page.11}{pernum} |Person number in sample weight| | \hyperlink{page.11}{11} | \hyperlink{page.11}{perwt} |IPUMS person weight| | \hyperlink{page.11}{11} | \hyperlink{page.11}{age} |Age in 1940| | \hyperlink{page.11}{11} | \hyperlink{page.11}{sex} |Sex in 1940| | \hyperlink{page.11}{11} | \hyperlink{page.11}{bpl} |Place of birth| | \hyperlink{page.11}{11} | \hyperlink{page.11}{mbpl} |Mother's place of birth| | \hyperlink{page.11}{11} | \hyperlink{page.11}{fbpl} |Father's place of birth| | \hyperlink{page.11}{11} | \hyperlink{page.11}{educd} |Educational attainment (detailed)| | \hyperlink{page.11}{11} | \hyperlink{page.11}{educ_yrs} |Educational attainment in years (constructed)| | \hyperlink{page.11}{11} | \hyperlink{page.11}{empstatd} |Employment status (detailed)| | \hyperlink{page.11}{11} | \hyperlink{page.11}{hispan} |Hispanic/Spanish/Latino origin| | \hyperlink{page.11}{11} | \hyperlink{page.11}{inconwg} |Had non-wage/salary income over $50| | \hyperlink{page.11}{11} | \hyperlink{page.11}{marst} |Marital status| | \hyperlink{page.11}{11} | \hyperlink{page.11}{nativity} |Foreign birthplace or parentage| | \hyperlink{page.11}{11} | \hyperlink{page.11}{occ} |Occupation| | \hyperlink{page.11}{11} | \hyperlink{page.11}{occscore} |Occupational income score| | \hyperlink{page.11}{11} | \hyperlink{page.11}{ownership} |Ownership of dwelling (tenure)| | \hyperlink{page.11}{11} | \hyperlink{page.11}{race} |Race| | \hyperlink{page.11}{11} | \hyperlink{page.11}{rent} |Montly contract rent| | \hyperlink{page.11}{11} | \hyperlink{page.11}{serial} |Household serial number| | \hyperlink{page.11}{11} | \hyperlink{page.11}{statefip} |State of residence 1940| | \hyperlink{page.11}{11} | \hyperlink{page.11}{urban} |Urban/rural status|
\vspace{50pt}
Summary: The CenSoc-DMF Version 2.1 Demo dataset (N = 70,211) links the IPUMS 1940 1% census sample to the Death Master File (DMF) dataset, a collection of death records reported to the Social Security Administration. Records were linked using the standard and conservative ABE method developed by Abramitzky, Boustan, and Eriksson (2012, 2014, 2017). Note, the demo file isn’t conducive to high-resolution mortality research, and we recommend researchers obtain a copy of the 1940 Census from IPUMS-USA and link on the individual-level, unique identifier HISTID variable.
\newpage
\huge HISTID \normalsize \vspace{12pt}
Label: Historical Unique Identifier
Description: HISTID is a unique individual-level identifier. It can be used to merge the CenSoc-DMF file with the 1940 Full-Count Census from IPUMS.
\newpage
\huge byear \normalsize \vspace{12pt}
Label: Birth Year
Description: byear reports a person's year of birth, as recorded in the Social Security Death Master File.
## Library Packages library(tidyverse) library(data.table) ## read in censoc_dmf_v2.1 data file censoc_dmf_v2.1<-read_csv("/data/censoc/censoc_data_releases/censoc_dmf_demo/censoc_dmf_demo_v2.1/censoc_dmf_demo_v2.1.csv")
byear_plot <- censoc_dmf_v2.1 %>% group_by(byear) %>% summarise(n = n()) %>% ggplot(aes(x = byear, y = n)) + geom_line() + geom_point() + theme_minimal(base_size = 15) + #replace with a different theme (theme_bw()) if the bbplot package isn't downloaded ggtitle("Year of Birth") + theme(legend.position="bottom") + xlab("title") + labs(x = "Year", y = "Count") + scale_y_continuous(labels = scales::comma) + scale_x_continuous(breaks = scales::pretty_breaks(n=5))
\vspace{75pt}
byear_plot
\newpage \huge bmonth \normalsize \vspace{12pt}
Label: Birth Month
Description: bmonth reports a person's month of birth, as recorded in the Social Security Death Master File.
## run in the console and copy and paste into documentation bmonth_tabulated <- knitr::kable(censoc_dmf_v2.1 %>% filter(bmonth != 0) %>% group_by(bmonth) %>% tally() %>% mutate(freq = signif(n*100 / sum(n), 2)) %>% mutate(label = c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December")) %>% select(bmonth, label, n, `freq %` = freq))
\vspace{30pt}
bmonth_tabulated
\newpage
\huge dyear \normalsize \vspace{12pt}
Label: Death Year
Description: dyear reports a person's year of death, as recorded in the Social Security Death Master File.
dyear_plot <- censoc_dmf_v2.1 %>% group_by(dyear) %>% summarise(n = n()) %>% ggplot(aes(x = dyear, y = n)) + geom_line() + geom_point() + theme_minimal(base_size = 15) + ggtitle("Year of Death") + theme(legend.position="bottom") + xlab("title") + labs(x = "Year", y = "Count") + scale_y_continuous(labels = scales::comma, limits = c(0, 3000)) + scale_x_continuous(breaks = scales::pretty_breaks(n=5))
\vspace{75pt}
dyear_plot
\newpage
\huge dmonth \normalsize \vspace{12pt}
Label: Death Month
Description: dmonth reports a person's month of death, as recorded in the Social Security Death Master File.
dmonth_tabulated <- knitr::kable(censoc_dmf_v2.1 %>% group_by(dmonth) %>% tally() %>% mutate(freq = signif(n*100 / sum(n), 2)) %>% mutate(label = c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December")) %>% select(dmonth, label, n, `freq %` = freq))
\vspace{30pt}
dmonth_tabulated
\newpage
\huge death_age \normalsize \vspace{12pt}
Label: Age at Death (Years)
Description: death_age reports a person's age at death in years, calculated using the birth and death information recorded in the Social Security Death Master File.
death_age_plot <- censoc_dmf_v2.1 %>% group_by(death_age) %>% summarise(n = n()) %>% ggplot(aes(x = death_age, y = n)) + geom_line() + geom_point() + theme_minimal(base_size = 15) + #replace with a different theme (theme_bw()) if the bbplot package isn't downloaded ggtitle("Age at Death") + theme(legend.position="bottom") + xlab("title") + labs(x = "Age at Death", y = "Count") + scale_y_continuous(labels = scales::comma) + scale_x_continuous(breaks = scales::pretty_breaks(n=5))
\vspace{75pt}
death_age_plot
\newpage
\huge link_abe_exact_conservative
\normalsize
\vspace{12pt}
Label: Flag for conservative ABE match
Description: A flag variable reporting whether a match was established with the ABE conservative match with exact names.
link_abe_exact_conservative_tabulated <- knitr::kable(censoc_dmf_v2.1 %>% group_by(link_abe_exact_conservative) %>% tally() %>% mutate(freq = signif(n*100 / sum(n), 3)) %>% arrange(desc(link_abe_exact_conservative)) %>% mutate(label = c("Conservative and Standard ABE Link", "Standard ABE Link Only")) %>% select(link_abe_exact_conservative, label, n, `freq %` = freq))
\vspace{50pt}
link_abe_exact_conservative_tabulated
\newpage
\huge weight \normalsize
\vspace{12pt}
Label: Sample Weights[^1]
Description: A post-stratification person-weight to Human Mortality Database (HMD) totals for persons (1) born between 1895-1939 (2) dying between 1975-2005 (3) dying between ages 65-100. Please see the CenSoc Methods Protocol for more details on weighting procedure.
[^1]: The IPUMS-USA 1940 1% sample also includes a weight (perweight) to account for the 1940 sampling procedure (thus no weights for the 100% complete count 1940 census). For analysis, we recommend using both sets of weights. A final weight can be constructed by multiplying the two weights together.
weights_tabulated <- censoc_dmf_v2.1 %>% filter(!is.na(weight)) %>% summarize('Min Weight' = round(min(weight),2), 'Max Weight' = round(max(weight), 2)) %>% mutate(id = 1:n()) %>% pivot_longer(-id, names_to = "Label", values_to = "Value") %>% select(Value, Label) %>% add_row(Label = "No Weight Assigned", Value = NA) %>% knitr::kable() weight.plot <- censoc_dmf_v2.1 %>% filter(!is.na(weight)) %>% ggplot() + geom_boxplot(aes(x=weight), fill='grey92') + ylim(-1,1) + theme_minimal(15) + theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) + ggtitle("Distribution of Weights") + xlab('Weight')
\vspace{50pt}
weights_tabulated
\vspace{50pt}
weight.plot
\newpage
\huge weight_conservative \normalsize
\vspace{12pt}
Label: Sample Weights (Conservative Sample)
Description: A post-stratification person-weight to Human Mortality Database (HMD) totals (only for matches established via the conservative ABE algorithm) for persons (1) born between 1895-1939 (2) dying between 1975-2005 (3) dying between ages 65-100. Please see the CenSoc Methods Protocol for more details on weighting procedure.
weights_conservtive_tabulated <- censoc_dmf_v2.1 %>% filter(link_abe_exact_conservative == 1) %>% filter(!is.na(weight_conservative)) %>% summarize('Min Weight' = round(min(weight_conservative),2), 'Max Weight' = round(max(weight_conservative), 2)) %>% mutate(id = 1:n()) %>% pivot_longer(-id, names_to = "Label", values_to = "Value") %>% select(Value, Label) %>% add_row(Label = "No Weight Assigned", Value = NA) %>% knitr::kable() weight_conservative.plot <- censoc_dmf_v2.1 %>% filter(link_abe_exact_conservative == 1) %>% filter(!is.na(weight_conservative)) %>% ggplot() + geom_boxplot(aes(x=weight_conservative), fill='grey92') + ylim(-1,1) + theme_minimal(15) + theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) + ggtitle("Distribution of Weights") + xlab('Weight')
\vspace{50pt}
weights_conservtive_tabulated
\vspace{50pt}
weight_conservative.plot
\newpage
\huge IPUMS 1940 Census Variable \normalsize
\vspace{12pt}
The variables below are from the IPUMS-USA 1940 1% census sample. We recommend looking at the terrific documentation on the IPUMS-USA website: \hyperlink{https://usa.ipums.org/usa/index.shtml}{https://usa.ipums.org/usa/index.shtml.}
| Variable | Label | |:-------------|:---------------------------------------------| | pernum |Person number in sample weight| |perwt |IPUMS person weight[^2] | | age |Age in 1940| | sex |Sex in 1940| | bpl |Place of birth| | mbpl |Mother's place of birth| | fbpl |Father's place of birth| | educd |Educational attainment (detailed)| | educ_yrs |Educational attainment in years (constructed)| | empstatd |Employment status (detailed)| | hispan |Hispanic/Spanish/Latino origin| | inconwg |Had non-wage/salary income over $50| | marst |Marital status| | nativity |Foreign birthplace or parentage| | occ |Occupation| | occscore |Occupational income score| | ownership |Ownership of dwelling (tenure)| | race |Race| | rent |Montly contract rent| | serial |Household serial number| | statefip |State of residence 1940| | urban |Urban/rural status|
[^2]: The perweight accounts for the 1940 sampling procedure to construct the 1% sample, and thus is only available in the 1940 1% sample. For analysis, we recommend using both the IPUMS perweight and the CenSoc weight. A final weight can be constructed by multiplying the two weights together
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Embedding an R snippet on your website
Add the following code to your website.
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