Divorce Statistics and Studies Blog

6 Stats Not to Trust: 6 Graphs, 6 Cartoons

Why Not to Trust Statistics

By Ben Orlin at mathwithbaddrawings.com

See also:

• What journalists, weather forecasters, and Han Solo get wrong about probability
• Headlines from a Mathematically Literate World 
• What Does Probability Mean in Your Profession?

 

Divorce rate NOT 50%: maybe 33% if current trends go on; 28.5% if educated, 38% if not; 17 to 42% depending on race

44% if Native American

42% if Black

37% if White

28.5% if Hispanic

17% if Asian 

 

Who gets divorced in America, in 7 charts

By Ana Swanson, April 6, 2016, on The Washington Post's Wonkblog

Based on 

Divorce Rates for Different Groups

POSTED TO DATA UNDERLOAD  by  NATHAN YAU on flowingdata.com

And on 

The Divorce Surge Is Over, but the Myth Lives On

 By Claire Cain Miller @clairecm DEC. 2, 2014 in The New York Times's "The Upshot"

 

Another story based on the same source:

See How Your Likelihood Of Divorce Changes With Age, Education, And Ethnicity

The most important finding? Contrary to popular belief, you are more likely to stay married than get divorced.

By CHARLIE SORREL, 04.05.16 on fastcoexist.com

Divorce/Margarine, Drowning/Marriage ... This Cluster of Correlations Couldn't be Coincidence

Divorce and margarine went in and (deservedly) out of fashion together, as everyone knows who thinks about it for a moment and is old enough to remember. And now, as marriage continues its long decline, Kentucky fishing-boat drownings do too, probably since marriage makes you want to go out alone in a small boat with nothing but a case of beer and your fishing gear. Seriously, how many of those guys out there fishing do you think are single? Single guys are probably somewhere where they're more likely to meet single women.

And yet Tyler VIgen refers to these and many others as "Spurious Correlations." These are among a top-ten list that also includes murders with hot objects, death from getting tangled in the bedsheets, Nicholas Cage movies, cheese-eating, moon-landing, suicide, Miss America,video games, killer spiders, spelling bees, and Ph.D.s.

Spurious Correlations

10 more here:

The 10 Most Bizarre Correlations

And here's ten that riff on another commonly reported form of statistic or study, not a correlation of change over time, but studies where a subset of respondents who have a particular response also show a different mixture of responses to a completely different question than is representative of the entire study pool. Stuff like, 60% of divorced people preferred chocolate ice cream compared to 80% of the general population.

10 Crazy Correlations Between Unrelated Things

By Gus Lubin and Tony Manfred

 

But wait, there's more correlations, marked in some damn good and genuinely important articles:

How a TV Sitcom Triggered the Downfall of Western Civilization

BY DAVID HOPKINS

 

And cutting a wider swath but coming to about the same conclusion, although blaming not sitcoms but the reality shows that mostly replaced them ...

Postapocalyptic hellscape by Jacob T. Levy

 

(h/t Jason Rylander and Todd Seavey) 

How to mislead with sloppy stats: The sex trafficking example

I don't know if any particular claims in this are true, or what "Truthout" is, but their description of all the definition-stretching and bait-and-switch tactics with statistics certainly rings true and provides vivid, compelling examples of something often observed in other fields.

Special Report: Money and Lies in Anti-Human Trafficking NGOs
Tuesday, 27 January 2015
By Anne Elizabeth Moore, Truthout

UK lifetime divorce rate by year-wed: 1963: 28%, High: 1986, 44%, Post-70s Low: 2008-present, 38%

You don't really know the divorce rate for a particular group of people until they're all dead. Or widowed. Most of what is offered as "divorce rates" are single-year per capita totals, pure "projections" predicting from recent trends, or the ratio of weddings to divorces in a single year and jurisdiction. As the UK's Marriage Foundation notes,"This 'year of divorce' method of calculating divorce rates makes analysis of trends all but impossible to assess because it mixes marriages of different durations." But once a cohort gets past the point where their chance of divorce becomes infinitesimal anyway, you can get a handle on it.

Of course, that assumes no great increase in the numbers of people divorcing after their silver anniversary. But it's still about the best method out there, and was undertaken recently in a study by the Marriage Foundation. And in fact the gray-divorce factor mentioned above as a caveat apparently does not apply in the UK: the researchers say divorce rates after the 10th anniversary have always been stable, with all the ups and downs in rates coming in the first 10 years of marriage. The study does seem to incorporate some element of lifetime projection and prediction, especially for newer marriages, but they do have those cohorts' records up until now to look at, as well as the stability in divorce rates for long marriages.

There are a few cohort-based studies in the U.S., which are some of the best explorations of divorce rates out there, but they are slightly less reliably because of middle-aged and elderly divorce, and because the collection and analysis of divorce statistics in the U.S. is relatively primitive, barely funded, and does not even cover several states, including California. Most studies tracking individuals and couples are done through the "long-form census" sent to a small but representative sample of the population, and even that has been threatened by budget cuts and by disdain from both the left and the libertarian right for government studies and records of marriage and family life.

This article about the study in The Daily Mail blames the 1969 no-fault laws for the increase, and seems to credit premarital cohabitation and rising marriage ages for the later improvements:

"Anyone who wed in 1986 has the highest chance in modern times of ending up divorced. In fact, researchers say almost half of those who married then will eventually split up. ... It was the first of six bleak years for marriage, during which the easy availability of divorce and the erosion of traditional family values meant that more couples parted than ever before or since. After 1991 the figure waned, until by 2008 – the year that produced the most stable marriages in recent times – the proportion of couples who will see their union end in divorce is put at well under the four out of ten mark.

"The study by the Marriage Foundation think tank gives a year-by-year breakdown of a couple’s chance of divorce, from the liberal 1960s and the explosion in numbers of marriage break-ups that followed.

Divorce law reforms in 1969 removed the idea that a husband or wife had to have been at fault from many cases, and introduced the ‘quickie’ divorce for those who admitted adultery or other faults.

Since the 1990s marriages have become more stable, with younger couples often choosing to live together before marriage, and those who do marry waiting until they are older, and then enjoying more long-lived unions.

Harry Benson of the Marriage Foundation said the average age for brides and grooms at their first wedding was 30 and 32 in 2011 – up from 23 and 25 in the early 1980s.

‘The entire rise and fall in divorce rates since the 1960s has taken place within the first decade of married life,’ he said. 

‘The worst two years to get married were 1986 and 1991. Some 44 per cent of couples who married in these years will end up divorced.’

The figures, based on Office for National Statistics marriage and divorce returns, revealed that in 1963 fewer than a third of weddings were due to lead to divorce – 28.2 per cent. But by 1977, following the 1969 reforms, the predicted risk of divorce for newly-marrieds had topped 40 per cent.

The 1986 peak was matched with 44.4 per cent predicted divorce levels for those marrying in 1988 and 1991. 

Then, gradually, divorce began to tail off and in 2008 bottomed out at 38.3 per cent. The lifetime likelihood of divorce for those married in 2012, the latest year for which figures are available, was 38.4 per cent."

Why 1986 was the worst year to get married: Nearly half of unions have ended in failure

• Those who wed in 1986 have highest chance in modern times of divorce
• Study by a think tank found 1991 was the second worst year to get married
• Since 1990, marriages have been more stable with couples moving in first

By STEVE DOUGHTY in THE DAILY MAIL, 11/30/15

Based on the Marriage Foundation study: Benson (2014), Early marriages stronger for 8th year running.

 Foundation press release

 

62% of psychology studies' results aren't as strong when experiments repeated

"Psychology Findings Not Strong as Claimed", by Benedict Carey in The New York Times 

 

To be clear, this replication study of 100 psychology studies did not reexamine their data and determine that the results were overstated; rather, it re-ran the experiments and found that 35 studies turned out the same, 62 produced the same outcomes, correlations, tendencies etc. but not as strongly as the original studies, and 3 were not counted because it was unclear how they turned out.

The stronger the results in the original study, the more likely they were to remain as strong when redone. The experience and prestige of the authors did not correlate positively or negatively with consistency of results.

The Times story also quotes some criticism of the replicators' methods and questioning of their rigor. But it does seem significant that 62% of retests showed weaker results, and apparently none showed stronger results,* and none showed completely different results, either.*

This certainly does seem to show some kind of tendency to overstate results, although it is hard to see how, since they are based directly on the data. And it appears that that tendency kicks in when the results are not that overwhelming in the first place. Or perhaps there are other factors that make the results stronger the first time an experiment is run and published? Or maybe results that are not so overwhelmingly one-sided are more likely to vary in different samples?

Perhaps more significant is that the experiments practically always ended up with the same conclusion, just not as strongly.*

"Social science isn't rocket science, it's harder",  Edward Tufte said when sharing the article on Facebook. But it's important to remember that this study was really designed for medical sciences, and was applied here to psychology studies. However, many social sciences, especially demographics, do not involve those kinds of studies, and sometimes reproducing results is not a possibility in many social science fields. While psychology studies are a significant share of the items on this blog, many more are demographic studies, polls, or in other disciplines of the social sciences.

__________

*Items marked with * are what I assume from the Times article, but it does not say so as explicitly as I would hope. I didn't look at the original study it reports on. I hope someone will do so, and post a comment saying whether these interpretations of the article are correct.

Wise questions on divorce stats & Goldilocks Theory: Are 30-something newlyweds really doomed?

Reporting on a correlation that was actually discovered several years ago, Joanna Rothkopf of Jezebel.com says what I've often thought but ne'er so well expressed, and which is rarely expressed at all, but deserves serious thought:

"But for real, how seriously are we supposed to take this? Studies keep claiming bullshit indicators are the keys to lasting marriages, including the price of the engagement ring (don’tspend between $2,000-4,000), amount of individual pre-marriage wealth, the size and price of the wedding and the presence of the honeymoon. So, I don’t know, just live your life."

The eminent marital statistician Nicholas Wolfinger describes what sound like very dramatic correlations between divorce and one's age at marriage:

“My data analysis shows that prior to age 32 or so, each additional year of age at marriage reduces the odds of divorce by 11 percent,” he writes. “However, after that the odds of divorce increase by 5 percent per year.” How come? Wolfinger isn't sure. But controlling the data for demographic and personal characteristics such as race, education, religion, sexual history, family background, or the size of the cities survey takers lived in didn't change the results, suggesting none of those factors could explain it. Ultimately, the professor suspects that there's a lot of self-selection at play: The sorts of people who wait a very long time to say "I do" just might not really be the marrying types, whether they realize it or not. Or, even if they are, their dating pool might have been whittled down to people who aren't.

Study: People Who Get Married After 32 Are More Likely To Get Divorced

By Joanna Rothkopf on Jezebel.com, 7/16/15

Based on:

• " Want to Avoid Divorce? Wait to Get Married, But Not Too Long" by @NickWolfinger on Family-Studies.org July 16, 2015
• " The Goldilocks Theory of Marriage" by Jordan Weissmann on Slate.com
• "Age at marriage and marital instability: revisiting the Becker–Landes–Michael hypothesis" by Evelyn L. Lehrer in the Journal of Population Economics, April 2008, Volume 21, Issue 2, pp 463-484, also dated 01 Sep 2006

 

Cohabiting parents almost triple, but children living with two married parents down only 4%, since 1996. Stats are funny that way.

Such are statistics. What almost tripled was the absolute number of unmarried cohabiting couples with children under it. What went down from 68% to 64% was the proportion of US children under 18 who lived with their two parents who were married and living together. Unchanged: children living with only the mother (24%), only the father (4%), or neither parent (4%).

Why are there such dramatically different ways of telling the same story? First, a smaller proportion is subject to change a lot more radically, relative to its former size, than a larger proportion is. When the number of states with a black senator doubled from 1 to 2,  the proportion of states without one only went down by 2%. Also, the first number used absolute numbers, which could also go up as population, and particularly the child population, increases.

Another big caveat: This study, like most statistics, substantially undercounts family disruption because it does not distinguish between the child's two actual parents, still married and/or still cohabiting, and one actual parent who's married to someone else who's referred to as a stepparent. "For this indicator, unless otherwise specified, a two-parent family refers to parents who are married to each other and living in the same household. They may be biological, adoptive, or stepparents. The Current Population Survey identifies all parents who are family or subfamily heads. Where cohabitants are concerned, until 2007, the CPS did not ask whether that person was also the parent of the child." Also, people are more likely to call themselves stepparents if they are married, not just cohabiting, so that is yet another distorting factor which increases the measurement of married parents versus cohabiting ones.

Ironically, the report's introductory section, titled "Importance", emphasizes how important the differences are between children living in truly intact married families and those who experience divorce or unwed birth and then live with stepparents. But in most cases, the government simply does not collect the data on that extremely important distinction, adding that insult to all the injuries done to marriage, families and children over the decades.

With that in mind, here are some excerpts. The article also has many useful links to many current sources of family statistics, the full study, and the underlying data.

Child Trends Databank. (2015). Family structure. 

The proportion of children living with both parents, following a marked decline between 1970 and 1990, has fallen more slowly over the most recent two decades, dropping from 69 percent in 2000 to 64 percent in 2014. ...

Between 1960 and 1996, the proportion of all children under age 18 who were living with two married parents decreased steadily, from 85 to 68 percent. This share was stable during much of the late 1990s and into the 2000s, but by 2012 it had decreased to 64 percent. The rate was stable between 2012 and 2014. 

In 1960, the proportion of children living in mother-only families was eight percent, but by 1996 that proportion had tripled, to 24 percent. Since then, it has fluctuated between 22 and 24 percent, and was at 24 percent in 2014. Between 1990 and 2013, the share of children living in father-only families has fluctuated between three and five percent, and was at four percent in 2014. The proportion living without either parent (with either relatives or with non-relatives) has remained steady, at approximately four percent. 

In 2014, there were 3.1 million cohabiting couples (unmarried) with children under 18. This number has been steadily increasing: in 1996, it was 1.2 million. ... Compared with married couples with children, cohabiting couples with children tend to be younger, less educated, lower–income, and with less secure employment. ...  In eight percent of unmarried couples with children, neither person was employed in 2014, compared with only four percent among married couples with children.

In 2014, 34 percent of black children were living with two parents, compared with 85 percent of Asian children, 75 percent of white children, and 58 percent of Hispanic children. 

[The following are from the introductory section, titled "Importance"]

Both mothers and fathers play important roles in the growth and development of children. The number and the type of parents (e.g., biological, step) in the household, as well as the relationship between the parents, are strongly linked to a child’s well-being. [1]  Among young children, for example, those living with no biological parents, or in single-parent households, are less likely than children with two biological parents to exhibit behavioral self-control, and more likely to be exposed to high levels of aggravated parenting, than are children living with two biological parents.[3] Children living with two married adults (biological or adoptive parents) have, in general, better health, greater access to health care, and fewer emotional or behavioral problems than children living in other types of families.[4]

Among children in two-parent families, those living with both biological parents in a low-conflict marriage tend to do better on a host of outcomes than those living in step-parent families. Outcomes for children in step-parent families are in many cases similar to those for children growing up in single-parent families.[5],[6] Children whose parents are divorced also have lower academic performance, social achievement, and psychological adjustment than children with married parents.[7] 

Single-parent families tend to have much lower incomes than do two-parent families, while cohabiting families fall in-between. Research indicates, however, that the income differential only partially accounts for the negative effects on many areas of child and youth well-being (including health, educational attainment and assessments, behavior problems, and psychological well-being) associated with living outside of a married, two-parent family.[9],[10]

 

Social & human sciences worse than useless from ignoring that "statistical significance" isn't PRACTICAL significance!

The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives, by Deirdre McCloskey and Stephen Ziliak, University of Michigan Press, argues that statistical significance in its all too common meaning, philosophical possibilities uncalibrated to the sizes of important effects in the world, is useless for science.

"Yet in medical science, in population biology, in much of sociology, political sciences, psychology, and economics, in parts of literary study, there reigns the spirit of the Mathematics or Philosophy Departments (appropriate in their own fields of absolutes). The result has been a catastrophe for such sciences, or former sciences. The solution is simple: get back to seeking oomph. It would be wrong, of course, to abandon math or statistics. But they need every time to be put into a context of How Much, as they are in chemistry, in most biology, in history, and in engineering science.

"In many of the life and human sciences the existence/whether question of the philosophical disciplines has substituted for the size-matters/how-much question of the scientific disciplines. The substitution is causing a loss of jobs, justice, profits, environment, and even life. The substitution we are worrying about here is called "statistical significance"—a qualitative, philosophical rule which has substituted for a quantitative, scientific magnitude."

I think this results from "scientism" -- from people in the social sciences and humanities, and in politics and the media, wishing to SOUND scientific and as a result failing to BE scientific, putting way too much stock in scientific terms they don't actually understand.

I know and admire Prof. McCloskey from her inspiring, interdisciplinary teaching at an Institute for Humane Studies seminar on "Liberty in Film and Fiction", a life-changing experience I'd recommend to any student.

ACS marriage/divorce data is crucial: leading family demographer @justinwolfers explains why

It's great to see my opinion on the proposed elimination of marital status from the long-form census confirmed, with much more understanding, context and background, by an eminent statistician and demographer, Justin Wolfers, in the New York Times! 

"Census Bureau’s Plan to Cut Marriage and Divorce Questions Has Academics Up in Arms" (NYT 12/31/14)

Wolfers reviews what the American Community Survey and its predecessors do about marriage and divorce, what other sources of data are out there and how they work (and don't work), and why the data is crucial for both progressives and conservatives who are concerned about families.