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

How Couples Meet and Stay Together (HCMST) is a study on how Americans meet their romantic partners. This is a nationally representative study of American adult respondents with no overlap in subjects from the original HCMST survey [ICPSR 30103] which was first fielded in 2009.

We study how couples allocate retirement-saving contributions across each spouse's account. In a new dataset covering over a million U.S. individuals, we find retirement contributions are not allocated to the account with the highest employer match rate. This lack of coordination—which goes against the assumptions of most models of household decision-making—is common, costly, persistent over time, and cannot be explained by inertia, auto-enrollment, or simple heuristics. Complementing the administrative evidence with an online survey, we find that inefficient allocations reflect both financial mistakes as well as deliberate choices—especially when trust and commitment inside the households are weak.

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 ---

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?

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