Funciones generales de las unidades orgánicas

To answer our first research question, we carry out latent class analysis (LCA) in Mplus to identity sub-groups, or classes, within our sample. Using this person- centered approach, we define classes of emerging adults who have experienced similar patterns of role dependence, progression, or boomeranging, over a two- year period, in their romantic relationships, education, employment, and living situation. LCA results are based on exploratory analyses, such that no assumptions are made beforehand about the structure of the classes. Rather we are guided by formal diagnostic statistics to choose the model which maximizes within class homogeneity and between class heterogeneity. Participants are then assigned to a class based on having the highest conditional probability of belonging to that class. We then use item probabilities to describe the classes. These refer to the probability that an individual assigned to a given class will have experienced a particular category of role dependence, progression, or boomeranging, in each domain. Covariates, gender, socioeconomic status, and ethnicity, are included in our latent class model. Class membership is then used to address our second research question. We first use it as independent variable, predicting emerging adult delinquent behavior, and then as a dependent variable predicted by adolescent delinquent behavior.

28 We only have access to self-reported offending data taken during emerging adulthood and police records taken during adolescence, hence using these two different types of delinquency measures. The data on police records was provided to us ready categorized; we do not have raw numbers of convictions available.

‘Boomeranging’ and delinquent behavior in emerging adulthood: A person-centered approach to studying role change

6.3.4 Missing data

As previously stated, the rate of participation at the fourth interview wave was 70%. In order to include the entire sample and avoid any bias which might result from using complete case analysis, missing values due to attrition were imputed, using a multiple imputation technique carried out in R (van Buuren, 2012). We first carried out the LCA on the sample with missing data from wave four interviews (N=652). The latent class analysis results presented here are therefore based on the proportion of our sample that completed the monthly status data in the fourth interview. Next, latent class membership, as well as self-reported delinquency at wave four, was imputed creating five datasets (N=970 in each dataset). The imputation model included data from all four interview waves, including monthly role status variables, self-reported delinquency, as well as demographic variables and a number of psychological self-report measures (see Appendix B for details of the imputation procedure). Following imputation, the results of subsequent analyses were pooled.

6.4 Results

In Table 2 the frequencies of the role dependence, progression, and boomeranging variables are displayed. In relationships, a third of our sample is single (33%), i.e., in a dependent role, and slightly over a third in or progressing into a relationship (37%). This leaves large minority (29%) experiencing boomeranging, i.e., at least one regressive move from being in relationship to being single over the two- year period. Over three quarters of our sample is stably in education, moves into education, or graduates during the study period (77%), with only 6% having left education without graduating prior to the start of the study. In this domain 17% of participants experienced boomeranging during the study period, i.e., leaving education without having graduated. In terms of employment, over half of the sample is in or progresses into employment during the study period (52%), with just 9% remaining unemployed throughout the period. Boomeranging is most prevalent in this domain: 40% of participants experience either moving from employment to unemployment or two or more changes in employment status during the study period. In living situation, 69% of our sample is still living dependently during the study period and 25% of the sample is living independently or progresses to independent living, either alone, with peers, or with a partner. Only a very small percentage experience boomeranging in their living situation during the study period (6%), suggesting that our participants generally remain dependent or progress in their living circumstances throughout the two-year period.

6

Table 2. Frequencies of dependence, progression, and boomeranging in each domain (prior to

multiple imputation).

Categories N(%)

Relationship N=652

0=stably single

1=in relationship or progress into relationship 2=at least one regression back into single status

217(33) 243(37) 192(29) Education

N=652

0=not in education and never graduated

1=in education, progress into education, progress out of education (graduating) 2=regression out of education (not graduated)

38(6) 504(77) 110(17) Employment N=652 0=stably unemployed

1=employed or progress into employment 2=at least one regression back to unemployment

57(9) 336(52) 259(40) Living situation

N=646

0=stably dependent living

1=independent living or progress independent living 2=at least one regression back into dependent living

446(69) 159(25) 41(6)

Table 3. Latent class model fit statistics (cl=class).

#par -2LL AIC BIC L2 _{df p Entropy BLRT (p) LMR-LRT (p)}

1cl 18 -5308.611 10653.222 10741.013 82.53 72 .1861 2cl 22 -2088.476 4220.951 4319.512 69.832 63 .2589 .66 -2164.908(<.001) 151.199(.0014) 3cl 36 -2066.014 4204.029 4365.31 70.582 54 .0644 .757 -2088.476(<.001) 44.433(.0156) 4cl 50 -2047.367 4194.734 4418.736 45.813 45 .4383 .693 -2066.367(.0714) 37.586(.794) 5cl 64 -2032.006 4192.012 4478.735 47.683 36 .0921 .707 -2047.23(.6667) 30.116(1) 6cl 78 -2030.528 4217.056 4566.5 48.227 27 .0072 .834 -2039.067(.667) 16.924(.5497)

Note: par = parameters, -2LL = Loglikelihood, AIC = Akaike Information Criterion, BIC = Bayesian

Information Criterion, L2 _{= Likelihood Ratio Chi-square, BLRT = Bootstrap Likelihood Ratio Test,}

LMR-LRT = Lo-Mendell-Rubin Likelihood Ratio Test.