SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES MARITAL STATUS - DP02 Universe - Population 15 Year and over Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 The marital status question is asked to determine the status of the person at the time of interview. Many government programs need accurate information on marital status, such as the number of married women in the labor force, elderly widowed individuals, or young single people who may establish homes of their own. The marital history data enables multiple agencies to more accurately measure the effects of federal and state policies and programs that focus on the well-being of families. Marital history data can provide estimates of marriage and divorce rates and duration, as well as flows into and out of marriage. This information is critical for more refined analyses of eligibility for program services and benefits, and of changes resulting from federal policies and programs.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The Urban Institute, in collaboration with Tahirih Justice Center, sought to examine forced marriages in the United States via an exploratory study of the victimization experiences of those subjected to and threatened with forced marriage. The study also sought to begin to understand elements at the intersection of forced marriage with intimate partner and sexual violence, such as: how perpetrators threaten and actually force victims into marriages; the elements of force, fraud, or coercion in the tactics used to carry out victimization; other case demographics and dynamics (e.g., overseas marriages versus those in the United States); factors that put individuals at risk of forced marriage or that trigger or elevate their risk of related abuses; help-seeking behavior; the role of social, cultural, and religious norms in forced marriage; and the ability (or lack thereof) of service providers, school officials, and government agencies with protection mandates (law enforcement, child protection, and social workers) to screen for, and respond to, potential and reported cases of forced marriage. This collection contains 1 Stata file: ICPSR-Data-File.dta (21007 cases; 48 variables). The qualitative data are not available as part of this data collection at this time.

Very Important

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Overview:

Explore the dataset and potentially gain valuable insight into your data science project through interesting features. The dataset was developed for a portfolio optimization graduate project I was working on. The goal was to the monetize risk of company deleveraging by associated with changes in economic data. Applications of the dataset may include. To see the data in action visit my analytics page. Analytics Page & Dashboard and to access all 295,000+ records click here.

• Mortgage-Backed Securities
• Geographic Business Investment
• Real Estate Analysis

For any questions, you may reach us at research_development@goldenoakresearch.com. For immediate assistance, you may reach me on at 585-626-2965. Please Note: the number is my personal number and email is preferred

Statistical Themes:

Note: in total there are 75 fields the following are just themes the fields fall under Home Owner Costs: Sum of utilities, property taxes.

• Second Mortgage: Households with a second mortgage statistics.
• Home Equity Loan: Households with a Home equity Loan statistics.
• Debt: Households with any type of debt statistics.
• Mortgage Costs: Statistics regarding mortgage payments, home equity loans, utilities and property taxes
• Home Owner Costs: Sum of utilities, property taxes statistics
• Gross Rent: Contract rent plus the estimated average monthly cost of utility features
• Gross Rent as Percent of Income Gross rent as the percent of income very interesting
• High school Graduation: High school graduation statistics.
• Population Demographics: Population demographic statistics.
• Age Demographics: Age demographic statistics.
• Household Income: Total income of people residing in the household.
• Family Income: Total income of people related to the householder.

Sources, if you wish to get the data your self :)

2012-2016 ACS 5-Year Documentation was provided by the U.S. Census Reports. Retrieved May 2, 2018, from

• Census estimate, error, and location data
• Census location information

Access All 325,258 Location of Our Most Complete Database Ever:

Providing you the potential to monetize risk and optimize your investment portfolio through quality economic features at unbeatable price. Access all 295,000+ records on an incredibly small scale, see links below for more details:

• Full Dataset: View Full Dataset
• Real Estate Research: View Research

The dataset is an index to digitized historical marriage licenses from 1908-1949 from all 5 NYC boroughs. Details about certificates in DORIS's collection and their digitization status can be found on our website (https://a860-historicalvitalrecords.nyc.gov/digital-vital-records).

The National Vital Statistics System (NVSS) data for the United States are provided through contracts between National Center for Health Statistics and vital registration systems operated in the various jurisdictions legally responsible for the registration of vital events (births, deaths, marriages, divorces, and fetal deaths).

The National Survey of Family Growth (NSFG) gathers information on family life, marriage and divorce, pregnancy, infertility, use of contraception, and men's and women's health. The survey results are used by the U.S. Department of Health and Human Services and others to plan health services and health education programs, and to do statistical studies of families, fertility, and health. Years included: 1973, 1976, 1982, 1988, 1995, 2002, 2006-2010; Data use agreement at time of file download:

Abstract

How Couples Meet and Stay Together (HCMST) is a study of how Americans meet their spouses and romantic partners.

• The study is a nationally representative study of American adults.
• 4,002 adults responded to the survey, 3,009 of those had a spouse or main
  romantic partner.
• The study oversamples self-identified gay, lesbian, and bisexual adults
• Follow-up surveys were implemented one and two years after the main survey, to study couple dissolution rates. Version 3.0 of the dataset includes two follow- up surveys, waves 2 and 3.
• Waves 4 and 5 are provided as separate data files that can be linked back to the main file via variable caseid_new.

The study will provide answers to the following research questions:

1. Do traditional couples and nontraditional couples meet in the same way? What kinds of couples are more likely to have met online?
2. Have the most recent marriage cohorts (especially the traditional heterosexual same-race married couples) met in the same way their parents and grandparents did?
3. Does meeting online lead to greater or less couple stability?
4. How do the couple dissolution rates of nontraditional couples compare to the couple dissolution rates of more traditional same-race heterosexual couples?
5. How does the availability of civil union, domestic partnership or same-sex marriage rights affect couple stability for same-sex couples? This study will provide the first nationally representative data on the couple dissolution rates of same-sex couples.

Methodology

Universe:

The universe for the HCMST survey is English literate adults in the U.S.

**Unit of Analysis: **

Individual

**Type of data collection: **

Survey Data

**Time of data collection: **

Wave I, the main survey, was fielded between February 21 and April 2, 2009. Wave 2 was fielded March 12, 2010 to June 8, 2010. Wave 3 was fielded March 22, 2011 to August 29, 2011. Wave 4 was fielded between March and November of 2013. Wave 5 was fielded between November, 2014 and March, 2015. Dates for the background demographic surveys are described in the User's Guide, under documentation below.

Geographic coverage:

United States of America

Smallest geographic unit:

US region

**Sample description: **

The survey was carried out by survey firm Knowledge Networks (now called GfK). The survey respondents were recruited from an ongoing panel. Panelists are recruited via random digit dial phone survey. Survey questions were mostly answered online; some follow-up surveys were conducted by phone. Panelists who did not have internet access at home were given an internet access device (WebTV). For further information about how the Knowledge Networks hybrid phone-internet survey compares to other survey methodology, see attached documentation.

The dataset contains variables that are derived from several sources. There are variables from the Main Survey Instrument, there are variables generated from the investigators which were created after the Main Survey, and there are demographic background variables from Knowledge Networks which pre-date the Main Survey. Dates for main survey and for the prior background surveys are included in the dataset for each respondent. The source for each variable is identified in the codebook, and in notes appended within the dataset itself (notes may only be available for the Stata version of the dataset).

Respondents who had no spouse or main romantic partner were dropped from the Main Survey. Unpartnered respondents remain in the dataset, and demographic background variables are available for them.

**Sample response rate: **

Response to the main survey in 2009 from subjects, all of whom were already in the Knowledge Networks panel, was 71%. If we include the the prior initial Random Digit Dialing phone contact and agreement to join the Knowledge Networks panel (participation rate 32.6%), and the respondents’ completion of the initial demographic survey (56.8% completion), the composite overall response rate is a much lower .326*.568*.71= 13%. For further information on the calculation of response rates, and relevant citations, see the Note on Response Rates in the documentation. Response rates for the subsequent waves of the HCMST survey are simpler, using the denominator of people who completed wave 1 and who were eligible for follow-up. Response to wave 2 was 84.5%. Response rate to wave 3 was 72.9%. Response rate to wave 4 was 60.0%. Response rate to wave 5 was 46%. Response to wave 6 was 91.3%. Wave 6 was Internet only, so people who had left the GfK KnowledgePanel were not contacted.

**Weights: **

See "Notes on the Weights" in the Documentation section.

Usage

When you use the data, you agree to the following conditions:

1. I will not use the data to identify individuals.
2. I will not charge a fee for the data if I distribute it to others.
3. I will inform the contact person abo

The estimated median household income and estimated median family income are two separate measures: every family is a household, but not every household is a family. According to the U.S. Census Bureau definitions of the terms, a family “includes a householder and one or more people living in the same household who are related to the householder by birth, marriage, or adoption,”[1] while a household “includes all the people who occupy a housing unit,” including households of just one person[2]. When evaluated together, the estimated median household income and estimated median family income provide a thorough picture of household-level economics in Champaign County.

Both estimated median household income and estimated median family income were higher in 2023 than in 2005. The changes in estimated median household income and estimated median family income between 2022 and 2023 were not statistically significant. Estimated median family income is consistently higher than estimated median household income, largely due to the definitions of each term, and the types of household that are measured and are not measured in each category.

Median income data was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes datasets on Median Household Income in the Past 12 Months (in 2020 Inflation-Adjusted Dollars) and Median Family Income in the Past 12 Months (in 2020 Inflation-Adjusted Dollars).

[1] U.S. Census Bureau. (Date unknown). Glossary. “Family Household.” (Accessed 19 April 2016).

[2] U.S. Census Bureau. (Date unknown). Glossary. “Household.” (Accessed 19 April 2016).

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (18 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (3 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (7 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (7 June 2021).;U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).

Research suggests that partisans are increasingly avoiding members of the other party—in their choice of neighborhood, social network, even their spouse. Leveraging a national database of voter registration records, we analyze 18 million households in the U.S. We find that three in ten married couples have mismatched party affiliations. We observe the relationship between inter-party marriage and gender, age, and geography. We discuss how the findings bear on key questions of political behavior in the US. Then, we test whether mixed-partisan couples participate less actively in politics. We find that voter turnout is correlated with the party of one’s spouse. A partisan who is married to a co-partisan is more likely to vote. This phenomenon is especially pronounced for partisans in closed primaries, elections in which non-partisan registered spouses are ineligible to participate.

Analysis of ‘Predicting Divorce’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/csafrit2/predicting-divorce on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Answers to certain questions can provide key information regarding if a couple is likely to get divorced in the future.

Content

Attribute Information:

Questions are ranked on a scale of 0-4 with 0 being the lowest and 4 being the highest. The last category states if the couple has divorced.

1. If one of us apologizes when our discussion deteriorates, the discussion ends.
2. I know we can ignore our differences, even if things get hard sometimes.
3. When we need it, we can take our discussions with my spouse from the beginning and correct it.
4. When I discuss with my spouse, to contact him will eventually work.
5. The time I spent with my wife is special for us.
6. We don't have time at home as partners.
7. We are like two strangers who share the same environment at home rather than family.
8. I enjoy our holidays with my wife.
9. I enjoy traveling with my wife.
10. Most of our goals are common to my spouse.
11. I think that one day in the future, when I look back, I see that my spouse and I have been in harmony with each other.
12. My spouse and I have similar values in terms of personal freedom.
13. My spouse and I have similar sense of entertainment.
14. Most of our goals for people (children, friends, etc.) are the same.
15. Our dreams with my spouse are similar and harmonious.
16. We're compatible with my spouse about what love should be.
17. We share the same views about being happy in our life with my spouse
18. My spouse and I have similar ideas about how marriage should be
19. My spouse and I have similar ideas about how roles should be in marriage
20. My spouse and I have similar values in trust.
21. I know exactly what my wife likes.
22. I know how my spouse wants to be taken care of when she/he sick.
23. I know my spouse's favorite food.
24. I can tell you what kind of stress my spouse is facing in her/his life.
25. I have knowledge of my spouse's inner world.
26. I know my spouse's basic anxieties.
27. I know what my spouse's current sources of stress are.
28. I know my spouse's hopes and wishes.
29. I know my spouse very well.
30. I know my spouse's friends and their social relationships.
31. I feel aggressive when I argue with my spouse.
32. When discussing with my spouse, I usually use expressions such as ‘you always’ or ‘you never’ .
33. I can use negative statements about my spouse's personality during our discussions.
34. I can use offensive expressions during our discussions.
35. I can insult my spouse during our discussions.
36. I can be humiliating when we discussions.
37. My discussion with my spouse is not calm.
38. I hate my spouse's way of open a subject.
39. Our discussions often occur suddenly.
40. We're just starting a discussion before I know what's going on.
41. When I talk to my spouse about something, my calm suddenly breaks.
42. When I argue with my spouse, ı only go out and I don't say a word.
43. I mostly stay silent to calm the environment a little bit.
44. Sometimes I think it's good for me to leave home for a while.
45. I'd rather stay silent than discuss with my spouse.
46. Even if I'm right in the discussion, I stay silent to hurt my spouse.
47. When I discuss with my spouse, I stay silent because I am afraid of not being able to control my anger.
48. I feel right in our discussions.
49. I have nothing to do with what I've been accused of.
50. I'm not actually the one who's guilty about what I'm accused of.
51. I'm not the one who's wrong about problems at home.
52. I wouldn't hesitate to tell my spouse about her/his inadequacy.
53. When I discuss, I remind my spouse of her/his inadequacy.
54. I'm not afraid to tell my spouse about her/his incompetence. **

Acknowledgements

Relevant Papers:

Yöntem, M , Adem, K , İlhan, T , Kılıçarslan, S. (2019). DIVORCE PREDICTION USING CORRELATION BASED FEATURE SELECTION AND ARTIFICIAL NEURAL NETWORKS. Nevşehir Hacı Bektaş Veli University SBE Dergisi, 9 (1), 259-273. Retrieved from [Web Link]

Citation Request:

Yöntem, M , Adem, K , İlhan, T , Kılıçarslan, S. (2019). DIVORCE PREDICTION USING CORRELATION BASED FEATURE SELECTION AND ARTIFICIAL NEURAL NETWORKS. Nevşehir Hacı Bektaş Veli University SBE Dergisi, 9 (1), 259-273. Retrieved from [Web Link]

Inspiration

What are the key indicators for divorce? Which questions/factors are most significant when predicting divorce?

--- Original source retains full ownership of the source dataset ---

In 2023, the average cost of a wedding reception venue in the United States amounted to an estimated 12,800 U.S. dollars. Couples in the U.S. have several costs to keep in mind when planning their special day. Besides the wedding ring, other expensive considerations typically include booking a live reception band and a wedding photographer, which cost an average of 4,300 and 2,900 U.S. dollars respectively in 2023.

Comprehensive dataset of 21,881 Wedding photographers in United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.