Category: Life-course criminology

A comment on Laub et al on marriage effects on crime

The just published Oxford Handbook of Developmental and Life Course Criminology includes an article where John Laub, Zachary Rowan and Robert Sampson gives an update on the age-graded theory of informal social control, which has dominated the field of life course criminology for the past couple of decades.

A key proposition of the theory is that life-course transitions can represent turning points in a criminal career, and marriage is the transition that has received the most attention in the empirical literature. A few years ago, I wrote a critical review together with my colleagues, Jukka Savolainen, Kjersti Aase and Torkild Lyngstad. In their book chapter, Laub et al are clearly critical of our review. I am a bit flattered that they bothered criticising us, but I do have a few comments.

First, Laub et al. correctly point out that we are unsatisfied with the existing studies considering estimating causal effects, and they do not really contradict our claim. Nevertheless, they point out that we “do not offer a viable alternative to build on this existing knowledge” (p 302). That might be right, but I do not think that is our responsibility either. I think those who advocate for a theory also has the responsibility for providing convincing empirical evidence.

Second, I think we actually did suggest a viable alternative. Importantly, we doubt that a causal effect of marriage on crime can be estimated at all, since it is hard to see how there might be any plausible exogenous variation. (I do not rule that out completely, but I am still waiting to see such a study). Instead, we suggest checking the preconditions for the theory to be true. For example, one suggested mechanism is that the spouse oppose criminal behaviour and exercises social control. If so, a survey of spouses’ attitudes to offending and how they react to their husband’s behaviour would provide relevant empirical evidence to the extent the premises for the theory are true. Providing any such evidence would make the theory more plausible. (If the spouses are favourable to crime and/or do not excertise any meaningful control over their husband, then that mechanism is not supported. Otherwise, it is corroborated). So, a viable alternative would be to check more carefully the preconditions empirically. It would still not provide an estimate of a causal effect, that is true, but it might be the best we can do.

Third, Laub, Zachry and Sampson states that “to rule out evidence that only comes from non-randomized experiments is to rule out most of criminology” (p 302). Now, that does not quite follow from our argument. Estimates of causal effects can only be provided if there is some kind of exogenous variation to be exploited. A causal theory can be corroborated in other ways, but it is not easy either. A careful descriptive study might provide evidence that are inconsistent with competing theories. Empirical findings that are equally consistent with a selection effect (or other competing theories), does not really count as a test of the theory.

Fourth, they refer to my joint work with Jukka Savolainen where we show that change occurs prior to employment rather than as a response to it, which Torkild Lyngstad and I also showed regarding the transition to marriage. Laub et al point out that Laub and Sampson (2003) acknowledge that ‘turning points’ are a part of a gradual process, and that turning points “are not a constant once set in motion, and they vary through time” (p 307). While this might sound reasonable, it also makes it a bit hard to understand what a turning point is. If changes in offending before marriage (or work) are consistent with the theory, then I am not sure it is possible to say when a turning point occurs. That makes it harder to empirically test the theory.

Fifth, Laub et al hint that since almost only studies using Norwegian register data shows the pattern of decline prior to a turning point, it might be something particular with the Norwegian setting. We actually suggested that the family formation patterns in the Nordic countries differ from the US in our review of research (see our article, page 438). While the context might indeed be important, that is not the main reason why so few other studies have found the same pattern. Actually, we argue that our findings are consistent with previously published results. Earlier studies should be repeated using an approach similar to what we did: just check the timing of change in offending relative to the transition in question. Until that is done, there is no basis for claiming the Norwegian patterns are any different from other contexts. (They might be, but we do not know yet).

Sixth, Laub et al discuss the role of cohabitation, and make a similar argument as we did in our review article: that the role of cohabitation is often a ‘trial-period’ or a ‘stepping stone’ towards marriage, and if it works out they will often marry. But Laub et al’s discussion of evidence focuses on whether the marriage effect translates into cohabiting couples, which is a discussion that does not take into account the point that marriage is an increasingly selective state, as well as it is becoming increasingly difficult to say when we should expect to see changes in offending.

In sum, I do apprechiate Laub et al. making an effort discussing specific arguments in our work. However, I am not quite convinced. I actually tend to think a romantic partner, a good job and generally changes in life situation might have an effect on crime. I find that reasonable, and I hope it is true. I am nevertheless not quite convinced by the empirical evidence, and I am hesitant to make claims about ‘turning points’. However, I do believe the empirical evidence can be improved through: 1) Check the timing of change, and 2) empirically investigate the specific preconditions for the mechanisms at work.

Moffitt review her own theory

Two days ago, Nature published a review article by Terrie Moffitt that “recaps the 25-year history of the developmental taxonomy of antisocial behaviour, concluding that it is standing the test of time…”

It should also be mentioned that the taxonomy has received quite a bit of criticism (which are not mentioned in Moffitt’s review), and I feel that also much of this critique is standing the test of time. It would have been a good thing if the 25^th anniversary of the taxonomy took the time to clear up some misunderstandings, controversies, and make some clarifications. However, Moffitt refrains from doing so, and I am not so sure the debate has moved forward. I have made some contributions to this debate, and I think my points are as relevant as ever. See here and here. It feels a bit wrong that they too stand the test of time. Importantly, so does the critique made by others.

In her recent review, she repeats what she also claimed in her 2006-review of evidence: a very large and important part of the empirical evidence supporting her theory is from studies using this latent trajectory models which. A key piece of evidence seems to be the identification of the hypothesized groups, as she states: “Since the advent of group-based trajectory modelling methods, the existence of trajectory groups fitting the LCP and AL taxonomy has now been confirmed by reviews of more than 100 longitudinal studies”. The method is a particular kind of latent class model for panel data. I would say this evidence is pretty weak. First of all, my discussion of trajectory models makes it clear that seemingly distinct groups can be detected in data where there are none. Since the further test of hypotheses relies on the identification of groups, these hypotheses are not reliable evidence either. The empirical evidence for the taxonomy is thus equally consistent with competing theories, and thus at best very weak evidence for either. Others have made similar points as well.

In her new article on page 4 she makes the claim group-based trajectory methods are capable of detecting hypothesized groups. The method does no such thing. It is a data reduction technique, which might be convenient for some purposes but it does not detect distinct groups. It creates some clusters, but it could equally well reflect an underlying continuous reality. Moreover, that the existence of these groups is confirmed across studies is so only if one accepts pretty much any evidence of heterogeneity in individual trajectories. As I pointed out in an article from 2009, the findings across studies are so divergent except that there is some kind of high-rate and low-rate groups, that it is hard to imagine any results from trajectory modelling that would not be taken in support of the taxonomy.

In short: At the best, the empirical evidence is consistent with the taxonomy. But this is largely uninformative as long as it is also consistent with pretty much all competing theories that acknowledge that different people behaves differently. The bottom line is that there are no evidence that there are qualitative differences between the “groups” (at least no such evidence are presented in Moffitt’s recent review). There might be quantitative differences, though.

The other risk factors she discusses and its relation to the groups could just as well be interpreted as differences in degree. However, on page 5, she dismisses that there might be quantitative rather than qualitative differences! (This is the closest to a clarification of whether she actually means literally distinct groups or not). Now, the evidence I have seen so far, shows that there are indeed differences between the average scores in the two groups, but most theories of criminal behaviour would expect higher scores on all risk factors for the highest-offending persons. While it sounds great that she proposed hypothesis in her 1993-article that have later proved correct – these hypothesis are also very general and consistent with other perspectives.

The key point here is that the empirical evidence is consistent with the taxonomy – and pretty much all other theories. It seems that the theory has not been put to a strict test in these 25 years. In a previous post, I made the following argument which holds generally:

I think (but I am not entirely sure), that in this context “testing a theory” only means findings that are consistent with a given theory. I think this is a generous use of the term “test”. I prefer to reserve the word “test” for situations where something is ruled out – or when using methods that at least in principle would be able to rule something out. In other words: If the findings are consistent with a theory but also consistent with one or several competing (or non-competing) theories, this is at best weak evidence for either theory. (This holds regardless of methods used). It is good that a theory is consistent with the empirical findings, but that is far from enough.

Second, in 2009 I wrote a more theoretical paper assessing the arguments in the taxonomic theory. A major point was that no argument are presented that there are distinct groups in the first place. However, one might argue that I have interpreted the theory too literally regarding the distinctness etc, so in this article, I also make an explicit discussion of this possibility. In 2009, I argued that since there are clearly some confusion regarding this issue, it would have been reasonable if someone (preferably Moffitt, of course) clarified if she really meant distinct groups or not. I am not aware any such clarification to date. But, as mentioned, she now goes a long way on dismissing the differences in degree interpretation (see her new article on page 5). I think the argument made by Sampson and Laub still holds: if LCP is just another term for high-rate, then the theory brings nothing new to the table. Indeed, all the mechanisms and risk-factors discussed are relevant and sound, but does not at all rely on a taxonomy as such.

In my view, the review should have concluded something like this: First, while much empirical evidence is consistent with the taxonomy, there is a lack of good evidence for the existence of groups. Second, there are still theoretical arguments that are unclear and needs specifications to allow for strict empirical tests. Nevertheless, the taxonomy has helped focusing on some important risk factors and mechanisms. (Although these factors were also known in 1993 according to Moffitt). Whether the taxonomy itself is needed to do so is less clear. Important work remains to be done.

What I am saying in some elaborate way is that the standards for what counts as empirical evidence in support of a hypothesis is too low. So is the precision level for “theories”. I know it is hard, but we should be able to do better.

PS Moffitt also refers to one of my articles on her first page when stating that “Chronic offenders are a subset of the 30–40% of males convicted of non-traffic crimes in developed nations”. My article says nothing of the kind, but tries to estimate how many will be convicted during their lifetime. It is just the wrong reference, but would of course recommend reading it 🙂

PPS I take the opportunity to also point out that while Nagin has previously claimed that my critique is simply based on a fundamental misunderstanding of his argument (see my comment on Nagin here), I have always argued, regardless of his position, that my methodological arguments are important because of how others – like Moffitt has just demonstrated – misunderstand the methods and the empirical results. Nagin also has a responsibility to clarify such prevalent misunderstandings.

The post Moffitt review her own theory appeared on The Grumpy Criminologist 2018-02-26 20:47:05 by Torbjørn.

Best practise of group-based modelling

I had initially decided to not pick more on group-based modelling, but here we go:

In his recent essay on group-based modelling in Journal of Research in Crime and Delinquency (see earlier posts here and here), Nagin discusses two examples of uses of group-based modelling in developmental criminology. It is not clear whether these are mentioned because they are particularly good examples, as they are presented as “early examples”. Maybe it is of historical interest, or these examples are mentioned because they are much cited. Since Nagin’s article is basically promoting GBTM, I assume these are mentioned because they are good examples of what can be achieved using this method. In any case, I would have liked to see examples where GBTM really made a difference.

The first example is the article by Nagin, Farrington and Moffitt who, according to Nagin using SPGM made an important contribution for the following reason:

…what was new from our analysis was the finding that low IQ also distinguished those following the low chronic trajectory from those following the adolescent limited and high chronic trajectories. This finding was made possible by the application of GBTM to identify the latent strata of offending trajectories present in the Cambridge data set.

The article by Nagin, Farrington and Moffitt shows that the relationship between IQ and delinquency varies over groups. (One could of course also say that the relationship is non-linear, but they stick to discussing groups). Which is fine, but the contribution is mainly how the groups are created – although some elaborate testing of equal parameters are involved. If other ways of summarizing the criminal careers (as either continuous or groups) would not find anything similar, it remains what is a methodological artefact and not. However, only one methodological approach was used, so it is hard to assess whether GBTM actually was the only way of discovering this kind of relationship. Maybe alternative methods (e.g. subjective classifications or a continuous index) would have found the exact same thing in these data? Could very well be.

The second example mentioned by Nagin is also written by himself together with Laub and Sampson. This is a very influential paper on the influence of marriage on crime, but has a major flaw because of how GBTM is used. I have recently written an review article together with Savolainen, Aase and Lyngstad on the marriage-crime literature published in Crime and Justice. We commented on this paper as follows:

…they estimated group-based trajectories (Nagin and Land 1993) for the entire observational period from age 7 to 32 and then assigned each person to a group on the basis of posterior probabilities. In the second
stage, they regressed the number of arrests in each 2-year interval from age 17 to 32 on changes in marital status and quality, controlling for group membership and other characteristics. In addition, they conducted separate regression analyses by trajectory group membership.
…
We are somewhat hesitant to endorse this conclusion for methodological reasons. Because the trajectories
were estimated over the entire period—including the marital period—controlling for group membership implies controlling for post-marriage offending outcomes as well. We expect this aspect of the analytic
strategy to bias the results, but further efforts are needed to assess the substantive implications of this methodological approach.

I think our final sentence of this quote very mild. They were partly conditioning on the outcome variable and that is bound to lead to trouble. Frankly, I do not know how to interpret these estimates. In this case, GBTM made a real difference, but to the worse. This was probably hard to see at the time since GBTM had not yet been subject to much methodological scrutiny yet. It is easier to see now.

In sum, although these two studies have other qualities, they are not examples of real success stories of GBTM. My advice would be to come up with some really good examples. But perhaps the only real success story of GBTM is Nagin and Lands 1993-article (for reasons given here).

P.S. Actually, I know of far better examples of using group-based modelling. Neither of them is dependent on GBTM, but it adds a nice touch. For example, Haviland et al use GBTM to improve propensity score matching. Another example is my own work with Jukka Savolainen where offending in the pre-job entry period is summarized using GBTM. For both these studies, other techniques could have been used, but GBTM works very well. There exist also other sound applications.

The post Best practise of group-based modelling appeared on The Grumpy Criminologist 2016-08-11 12:36:42 by Torbjørn.