Journal of Traumatic Stress August 2014, 27, 388–396
Dissociation and Posttraumatic Stress Disorder: A Latent Profile Analysis Christy A. Blevins, Frank W. Weathers, and Tracy K. Witte Department of Psychology, Auburn University, Auburn, Alabama, USA
The fifth edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013) contains a dissociative subtype for posttraumatic stress disorder (PTSD) characterized by significant depersonalization and derealization. In this study the PTSD dissociative subtype was examined using latent profile analysis in a sample of 541 trauma-exposed college students. Items from the PTSD Checklist and Multiscale Dissociation Inventory were used as latent class indicators. Results supported a 3-class solution including a well-adjusted class, a PTSD class, and a PTSD/dissociative class characterized by elevated symptoms of PTSD, depersonalization, and derealization. Significant class differences were found on a number of measures of related psychopathology with Cohen’s d effect size estimates ranging from 0.04 to 1.86. Diagnostic and treatment implications regarding the dissociative subtype are discussed.
The fifth edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association [APA], 2013) contains a dissociative subtype for posttraumatic stress disorder (PTSD) characterized by prominent depersonalization (feelings of unreality or detachment regarding one’s self) and derealization (feelings of unreality or detachment regarding one’s environment). This change was motivated by a long history of clinical observation and empirical investigation linking trauma and dissociation (for a review, see Carlson, Dalenberg, & McDade-Montez, 2012), neurobiological research demonstrating differential response patterns in patients with PTSD with predominantly reexperiencing versus dissociative responses to trauma imagery (e.g., Lanius, Brand, Vermetten, Frewen, & Spiegel, 2012), and cross-cultural research demonstrating distinctions between individuals with PTSD reporting high and low dissociation (Stein et al., 2013). This putative subtype also has been examined using taxometrics (e.g., Waelde, Silvern, & Fairbank, 2005) and latent profile analysis (LPA; Steuwe, Lanius, & Frewen, 2012; Wolf, Miller, et al., 2012; Wolf, Lunney, et al., 2012). LPA is particularly promising because it identifies classes of individuals based on similarities in responses to a set of observable indicators. Unlike cluster analysis, which also classifies individuals, LPA is based on a statistical model, provides objective tests to determine model identifica-
tion, and does not require decisions regarding scaling of observed variables (Vermunt & Magidson, 2002). To date, we are aware of three studies that have used LPA to identify a PTSD dissociative subtype. First, Wolf, Miller, et al. (2012) classified trauma-exposed veterans and their intimate partners using PTSD and dissociation items from the ClinicianAdministered PTSD Scale (CAPS; Blake et al., 1995). The best-fitting class solution included low PTSD/low dissociation, high PTSD/low dissociation, and high PTSD/high dissociation classes. The PTSD/dissociative class (6% of the sample) had higher scores than the PTSD class on flashbacks, depersonalization, and derealization, and greater exposure to sexual trauma. Second, Wolf, Lunney, et al. (2012) found a similar 3-class solution using the CAPS in independent samples of male and female veterans. In male veterans, the PTSD/dissociative class (15.6%) had higher scores than the PTSD class on exaggerated startle, depersonalization, and derealization. In female veterans, the PTSD/dissociative class (29.9%) had lower scores than the PTSD class on trauma-cued emotional distress and physiological reactivity, higher scores on Trauma Symptom Inventory (Briere, 1995) depersonalization and derealization items, and a higher prevalence of avoidant and borderline personality disorders. Third, using the CAPS in a female civilian sample, Steuwe et al. (2012) found a similar 3-class solution, with moderate PTSD/low dissociation, high PTSD/low dissociation, and high PTSD/high dissociation classes. The PTSD/dissociative class (25.5%) had higher scores than the PTSD class on depersonalization and derealization—but importantly not on any core PTSD symptoms—as well as higher Dissociative Experiences Scale (DES; Bernstein & Putnam, 1986) scores, greater exposure to physical and sexual abuse, and a higher prevalence of depression and specific phobias.
Correspondence concerning this article should be addressed to Frank Weathers, Department of Psychology, 226 Thach Hall, Auburn University, Auburn, AL 36849. E-mail: [email protected] C 2014 International Society for Traumatic Stress Studies. View Copyright this article online at wileyonlinelibrary.com DOI: 10.1002/jts.21933
388
Dissociation and Posttraumatic Stress Disorder
In sum, these LPA studies examining PTSD and dissociation have converged on a 3-class solution, with a distinctive PTSD/dissociative class constituting 6.0%–29.9% of the samples. Findings, however, are mixed regarding which, if any, PTSD symptoms differentiate the PTSD and PTSD/dissociative classes. This study sought to replicate and extend these findings in trauma-exposed college students. The first aim was to improve the assessment of dissociation by using the Multiscale Dissociation Inventory (MDI; Briere, 2002), a focal dissociation measure. The second aim was to examine class differences in PTSD and dissociative symptoms. The final aim was to examine class differences on external measures of psychopathology. Four main hypotheses were evaluated. First (Hypothesis 1), we hypothesized that LPA using the PTSD Checklist (PCL; Weathers, Litz, Herman, Huska, & Keane, 1993) and MDI items as latent class indicators would support a 3-class solution, yielding low PTSD/low dissociation (well-adjusted), high PTSD/low dissociation (PTSD), and high PTSD/high dissociation (PTSD/dissociative) classes. Second (Hypothesis 2), we hypothesized the PTSD and PTSD/dissociative classes would have higher PTSD severity than the well-adjusted class. In addition, we predicted the PTSD/dissociative class would have higher scores than the PTSD class on PTSD symptoms most related to dissociation, i.e., flashbacks and amnesia. Third (Hypothesis 3), we hypothesized that the PTSD/dissociative class would have higher depersonalization/derealization severity than the PTSD and well-adjusted classes. Specifically, we predicted the PTSD/dissociative class would have higher scores than the PTSD class on items describing severe depersonalization/derealization (e.g., out of body experiences), but comparable scores on items overlapping with PTSD emotional numbing symptoms. Fourth (Hypothesis 4), we hypothesized that (a) the PTSD and PTSD/dissociative classes would have higher overall levels of psychopathology than the well-adjusted class; (b) the PTSD/dissociative class would have higher scores than the PTSD class on scales measuring constructs closely related to dissociation, including borderline features, somatization, and facets of the schizophrenia spectrum; and (c) the PTSD and PTSD/dissociative classes would not differ on scales measuring constructs less associated with dissociation and PTSD, e.g., mania and antisocial personality features.
Method Participants and Procedure Participants were 541 undergraduates at a large public university in the southeastern United States. The study was approved by the Auburn University Institutional Review Board. Participants were recruited with an advertisement that described the study as involving the assessment of stressful life events. Inclusion in final analyses required participants to endorse at least one event meeting PTSD Criterion A1 of the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSMIV-TR; APA, 2000) on the Life Events Checklist (LEC), the
389
self-report trauma assessment of the CAPS (Blake et al., 1995). Of 635 participants who completed the study, 94 (14.8%) were excluded because their index event did not meet Criterion A1. After providing written informed consent, participants completed an online self-report battery including the LEC and several measures of PTSD and dissociation. Some (n = 243) also completed the Personality Assessment Inventory (PAI; Morey, 2007) after completing the initial battery. Data from a subset of the current sample have been reported in two previous studies (Blevins, Weathers, & Mason, 2012; Blevins, Witte, & Weathers, 2013). The sample was predominantly female (67.1%) and Caucasian (80.0%) or African American (13.2%). Age ranged from 18 years to 32 years (M = 20.21, SD = 1.64). Trauma types reported included sudden violent or unexpected death (30.4%), transportation or other serious accident (21.8%), physical or sexual assault (17.9%), life-threatening illness or injury (9.8%), natural disaster (7.1%), and other (13.0%). Most participants (70.9%) reported multiple traumatic events. Measures Seventeen PTSD and 10 dissociative symptom items were used as latent class indicators. PTSD was assessed with the PCL-S, the specific version of the PCL, a self-report measure corresponding to DSM-IV-TR PTSD symptoms. Respondents indicate how much they have been bothered by symptoms in the past month on a 5-point scale (1 = not at all, 5 = extremely). The PCL-S has excellent psychometric properties (Wilkins, Lang, & Norman, 2011). The internal consistency for the PCLS in this sample was high (Cronbach’s α = .94). Dissociation was assessed with five depersonalization and five derealization items of the MDI (Briere, 2002). Respondents indicate symptom frequency in the past month on a 5-point scale (1 = never, 5 = very often). The MDI has strong psychometric properties (Briere, 2002; Blevins et al., 2012). The internal consistency (α) for MDI depersonalization and derealization scales in this sample was .84 and .85, respectively. The remaining scales on the MDI were used as correlates of class membership (α = .78 to .93). Several additional measures of trauma exposure, dissociation, and related psychopathology were administered as external correlates of class membership. Trauma exposure was assessed with the LEC, which includes 17 categories of potentially traumatic events. Respondents indicate whether they have experienced, witnessed, or learned about each event category. The LEC has good psychometric properties (Gray, Litz, Hsu, & Lombardo, 2004). The DES and Cambridge Depersonalization Scale (CDS; Sierra & Berrios, 2000) were administered as additional dissociation measures. The DES is a 28-item self-report measure of dissociation. Respondents indicate symptom frequency from 0– 100% in increments of 10%. Factor analytic studies indicate a 3-factor structure including amnesia, absorption, and depersonalization/derealization factors (Stockdale, Gridley, Balogh, &
Journal of Traumatic Stress DOI 10.1002/jts. Published on behalf of the International Society for Traumatic Stress Studies.
390
Blevins et al.
Table 1 Descriptive Statistics for PCL-S and MDI Scale PCL-S Total MDI Depersonalization MDI Derealization
No. of items
Possible range
Observed range
M
SD
Interitem correlations
17 5 5
17–85 5–25 5–25
17–83 5–24 5–25
35.75 6.67 7.97
15.11 2.89 3.49
.18 – .75 .37 – .68 .33 – .70
Note. N = 541. PCL-S = PTSD Checklist, specific version; MDI = Multiscale Dissociation Inventory.
Holtgraves, 2002). DES total and subscale scores were analyzed in the present study. Cronbach’s α for DES total and subscale scores in this sample ranged from .79 to .94. The CDS is a 29-item self-report measure of depersonalization/derealization symptoms. Respondents indicate symptom frequency (0 = never to 4 = all the time) and duration (1 = few seconds to 6 = more than a week). Although previous factor analytic studies proposed 4- and 5-factor models, a recent study supported a 2-factor model including unreality and numbing (Blevins et al., 2013). The CDS total scale and unreality and numbing subscales were analyzed in the present study. Cronbach’s α for CDS total and subscale scores in this sample ranged from .89 to .93. The PAI, a 344-item multiscale inventory assessing a wide range of psychopathology, was administered to provide additional external correlates. Respondents rate each item on a 4-point scale (0 = False to 3 = Very True). The PAI clinical scales have excellent psychometric properties (Morey, 2007) and demonstrated adequate internal consistency in this sample (α = .75 to .90). Data Analysis Data analyses were conducted using a 3-step approach to latent class estimation and evaluation of the relationship between class membership and external correlates. As described by Asparouhov and Muth´en (2013), in the first step the latent class model is estimated using only latent class indicators. Then, most likely class membership is calculated using the latent class posterior distribution estimated in the first step, taking into account the rate of classification uncertainty. Last, most likely class membership is used to examine class differences on external correlates not included in the latent model. The statistical significance of conditional class specific mean
differences was evaluated by calculating Wald tests of mean equality, which can be used for both binary and continuous variables. We specified external correlates as continuous distal outcomes with unequal means and variances in each class. A recent simulation study demonstrated superiority of the 3-step approach over other similar methods (Asparouhov & Muth´en, 2013). PCL-S and MDI depersonalization and derealization items were submitted to LPA using the Mplus Version 7 (Muth´en & Muth´en, 1998–2012) mixture modeling procedure, with the robust maximum likelihood (MLR) estimator. Missing data were addressed using full information maximum likelihood (FIML), and acceptable covariance coverage was found (98.0% to 99.8% for latent class indicators, 36.0% to 98.0% for external correlates; Enders & Bandalos, 2001). FIML outperforms alternative methods for handling missing data across simulation studies, particularly when data are not missing completely at random and missing data rates are high (Enders, 2010). Based on previous LPA studies examining the dissociative subtype, a 3-class model was specified and compared to 2-, 4-, 5-, and 6-class models. First, models were examined with regard to overall quality and adequate convergence. Then, models were compared using a set of fit indices: (a) Bayesian information criterion (BIC; McLachlan & Peel, 2000), with lower values indicating better fit; (b) the Vuong-Lo-Mendell-Rubin adjusted likelihood ratio test (LRT-A; Lo, Mendell & Rubin, 2001); and (c) the bootstrapped likelihood ratio test (BLRT; Nylund, Asparouhov, & Muth´en, 2007), with significant p values suggesting the specified model provides better fit compared to a model with one fewer class. In addition, models were compared on entropy (Muth´en, 2004), with values closer to 1.0 indicating better classification quality, profile uniqueness, and theoretical considerations. Last, classes from the best-fitting model were compared on external correlates. Overall tests of
Table 2 Fit Indices for Competing Latent Class Models Model
Log-likelihood
BIC
Entropy
LMR-A p
BLRT p
2 Class 3 Class 4 Class
−19,419.23 −18,677.96 −18,226.11
39,354.52 38,048.20 37,320.71
.96 .96 .97
Dissociation and Posttraumatic Stress Disorder: A Latent Profile Analysis Christy A. Blevins, Frank W. Weathers, and Tracy K. Witte Department of Psychology, Auburn University, Auburn, Alabama, USA
The fifth edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013) contains a dissociative subtype for posttraumatic stress disorder (PTSD) characterized by significant depersonalization and derealization. In this study the PTSD dissociative subtype was examined using latent profile analysis in a sample of 541 trauma-exposed college students. Items from the PTSD Checklist and Multiscale Dissociation Inventory were used as latent class indicators. Results supported a 3-class solution including a well-adjusted class, a PTSD class, and a PTSD/dissociative class characterized by elevated symptoms of PTSD, depersonalization, and derealization. Significant class differences were found on a number of measures of related psychopathology with Cohen’s d effect size estimates ranging from 0.04 to 1.86. Diagnostic and treatment implications regarding the dissociative subtype are discussed.
The fifth edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association [APA], 2013) contains a dissociative subtype for posttraumatic stress disorder (PTSD) characterized by prominent depersonalization (feelings of unreality or detachment regarding one’s self) and derealization (feelings of unreality or detachment regarding one’s environment). This change was motivated by a long history of clinical observation and empirical investigation linking trauma and dissociation (for a review, see Carlson, Dalenberg, & McDade-Montez, 2012), neurobiological research demonstrating differential response patterns in patients with PTSD with predominantly reexperiencing versus dissociative responses to trauma imagery (e.g., Lanius, Brand, Vermetten, Frewen, & Spiegel, 2012), and cross-cultural research demonstrating distinctions between individuals with PTSD reporting high and low dissociation (Stein et al., 2013). This putative subtype also has been examined using taxometrics (e.g., Waelde, Silvern, & Fairbank, 2005) and latent profile analysis (LPA; Steuwe, Lanius, & Frewen, 2012; Wolf, Miller, et al., 2012; Wolf, Lunney, et al., 2012). LPA is particularly promising because it identifies classes of individuals based on similarities in responses to a set of observable indicators. Unlike cluster analysis, which also classifies individuals, LPA is based on a statistical model, provides objective tests to determine model identifica-
tion, and does not require decisions regarding scaling of observed variables (Vermunt & Magidson, 2002). To date, we are aware of three studies that have used LPA to identify a PTSD dissociative subtype. First, Wolf, Miller, et al. (2012) classified trauma-exposed veterans and their intimate partners using PTSD and dissociation items from the ClinicianAdministered PTSD Scale (CAPS; Blake et al., 1995). The best-fitting class solution included low PTSD/low dissociation, high PTSD/low dissociation, and high PTSD/high dissociation classes. The PTSD/dissociative class (6% of the sample) had higher scores than the PTSD class on flashbacks, depersonalization, and derealization, and greater exposure to sexual trauma. Second, Wolf, Lunney, et al. (2012) found a similar 3-class solution using the CAPS in independent samples of male and female veterans. In male veterans, the PTSD/dissociative class (15.6%) had higher scores than the PTSD class on exaggerated startle, depersonalization, and derealization. In female veterans, the PTSD/dissociative class (29.9%) had lower scores than the PTSD class on trauma-cued emotional distress and physiological reactivity, higher scores on Trauma Symptom Inventory (Briere, 1995) depersonalization and derealization items, and a higher prevalence of avoidant and borderline personality disorders. Third, using the CAPS in a female civilian sample, Steuwe et al. (2012) found a similar 3-class solution, with moderate PTSD/low dissociation, high PTSD/low dissociation, and high PTSD/high dissociation classes. The PTSD/dissociative class (25.5%) had higher scores than the PTSD class on depersonalization and derealization—but importantly not on any core PTSD symptoms—as well as higher Dissociative Experiences Scale (DES; Bernstein & Putnam, 1986) scores, greater exposure to physical and sexual abuse, and a higher prevalence of depression and specific phobias.
Correspondence concerning this article should be addressed to Frank Weathers, Department of Psychology, 226 Thach Hall, Auburn University, Auburn, AL 36849. E-mail: [email protected] C 2014 International Society for Traumatic Stress Studies. View Copyright this article online at wileyonlinelibrary.com DOI: 10.1002/jts.21933
388
Dissociation and Posttraumatic Stress Disorder
In sum, these LPA studies examining PTSD and dissociation have converged on a 3-class solution, with a distinctive PTSD/dissociative class constituting 6.0%–29.9% of the samples. Findings, however, are mixed regarding which, if any, PTSD symptoms differentiate the PTSD and PTSD/dissociative classes. This study sought to replicate and extend these findings in trauma-exposed college students. The first aim was to improve the assessment of dissociation by using the Multiscale Dissociation Inventory (MDI; Briere, 2002), a focal dissociation measure. The second aim was to examine class differences in PTSD and dissociative symptoms. The final aim was to examine class differences on external measures of psychopathology. Four main hypotheses were evaluated. First (Hypothesis 1), we hypothesized that LPA using the PTSD Checklist (PCL; Weathers, Litz, Herman, Huska, & Keane, 1993) and MDI items as latent class indicators would support a 3-class solution, yielding low PTSD/low dissociation (well-adjusted), high PTSD/low dissociation (PTSD), and high PTSD/high dissociation (PTSD/dissociative) classes. Second (Hypothesis 2), we hypothesized the PTSD and PTSD/dissociative classes would have higher PTSD severity than the well-adjusted class. In addition, we predicted the PTSD/dissociative class would have higher scores than the PTSD class on PTSD symptoms most related to dissociation, i.e., flashbacks and amnesia. Third (Hypothesis 3), we hypothesized that the PTSD/dissociative class would have higher depersonalization/derealization severity than the PTSD and well-adjusted classes. Specifically, we predicted the PTSD/dissociative class would have higher scores than the PTSD class on items describing severe depersonalization/derealization (e.g., out of body experiences), but comparable scores on items overlapping with PTSD emotional numbing symptoms. Fourth (Hypothesis 4), we hypothesized that (a) the PTSD and PTSD/dissociative classes would have higher overall levels of psychopathology than the well-adjusted class; (b) the PTSD/dissociative class would have higher scores than the PTSD class on scales measuring constructs closely related to dissociation, including borderline features, somatization, and facets of the schizophrenia spectrum; and (c) the PTSD and PTSD/dissociative classes would not differ on scales measuring constructs less associated with dissociation and PTSD, e.g., mania and antisocial personality features.
Method Participants and Procedure Participants were 541 undergraduates at a large public university in the southeastern United States. The study was approved by the Auburn University Institutional Review Board. Participants were recruited with an advertisement that described the study as involving the assessment of stressful life events. Inclusion in final analyses required participants to endorse at least one event meeting PTSD Criterion A1 of the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSMIV-TR; APA, 2000) on the Life Events Checklist (LEC), the
389
self-report trauma assessment of the CAPS (Blake et al., 1995). Of 635 participants who completed the study, 94 (14.8%) were excluded because their index event did not meet Criterion A1. After providing written informed consent, participants completed an online self-report battery including the LEC and several measures of PTSD and dissociation. Some (n = 243) also completed the Personality Assessment Inventory (PAI; Morey, 2007) after completing the initial battery. Data from a subset of the current sample have been reported in two previous studies (Blevins, Weathers, & Mason, 2012; Blevins, Witte, & Weathers, 2013). The sample was predominantly female (67.1%) and Caucasian (80.0%) or African American (13.2%). Age ranged from 18 years to 32 years (M = 20.21, SD = 1.64). Trauma types reported included sudden violent or unexpected death (30.4%), transportation or other serious accident (21.8%), physical or sexual assault (17.9%), life-threatening illness or injury (9.8%), natural disaster (7.1%), and other (13.0%). Most participants (70.9%) reported multiple traumatic events. Measures Seventeen PTSD and 10 dissociative symptom items were used as latent class indicators. PTSD was assessed with the PCL-S, the specific version of the PCL, a self-report measure corresponding to DSM-IV-TR PTSD symptoms. Respondents indicate how much they have been bothered by symptoms in the past month on a 5-point scale (1 = not at all, 5 = extremely). The PCL-S has excellent psychometric properties (Wilkins, Lang, & Norman, 2011). The internal consistency for the PCLS in this sample was high (Cronbach’s α = .94). Dissociation was assessed with five depersonalization and five derealization items of the MDI (Briere, 2002). Respondents indicate symptom frequency in the past month on a 5-point scale (1 = never, 5 = very often). The MDI has strong psychometric properties (Briere, 2002; Blevins et al., 2012). The internal consistency (α) for MDI depersonalization and derealization scales in this sample was .84 and .85, respectively. The remaining scales on the MDI were used as correlates of class membership (α = .78 to .93). Several additional measures of trauma exposure, dissociation, and related psychopathology were administered as external correlates of class membership. Trauma exposure was assessed with the LEC, which includes 17 categories of potentially traumatic events. Respondents indicate whether they have experienced, witnessed, or learned about each event category. The LEC has good psychometric properties (Gray, Litz, Hsu, & Lombardo, 2004). The DES and Cambridge Depersonalization Scale (CDS; Sierra & Berrios, 2000) were administered as additional dissociation measures. The DES is a 28-item self-report measure of dissociation. Respondents indicate symptom frequency from 0– 100% in increments of 10%. Factor analytic studies indicate a 3-factor structure including amnesia, absorption, and depersonalization/derealization factors (Stockdale, Gridley, Balogh, &
Journal of Traumatic Stress DOI 10.1002/jts. Published on behalf of the International Society for Traumatic Stress Studies.
390
Blevins et al.
Table 1 Descriptive Statistics for PCL-S and MDI Scale PCL-S Total MDI Depersonalization MDI Derealization
No. of items
Possible range
Observed range
M
SD
Interitem correlations
17 5 5
17–85 5–25 5–25
17–83 5–24 5–25
35.75 6.67 7.97
15.11 2.89 3.49
.18 – .75 .37 – .68 .33 – .70
Note. N = 541. PCL-S = PTSD Checklist, specific version; MDI = Multiscale Dissociation Inventory.
Holtgraves, 2002). DES total and subscale scores were analyzed in the present study. Cronbach’s α for DES total and subscale scores in this sample ranged from .79 to .94. The CDS is a 29-item self-report measure of depersonalization/derealization symptoms. Respondents indicate symptom frequency (0 = never to 4 = all the time) and duration (1 = few seconds to 6 = more than a week). Although previous factor analytic studies proposed 4- and 5-factor models, a recent study supported a 2-factor model including unreality and numbing (Blevins et al., 2013). The CDS total scale and unreality and numbing subscales were analyzed in the present study. Cronbach’s α for CDS total and subscale scores in this sample ranged from .89 to .93. The PAI, a 344-item multiscale inventory assessing a wide range of psychopathology, was administered to provide additional external correlates. Respondents rate each item on a 4-point scale (0 = False to 3 = Very True). The PAI clinical scales have excellent psychometric properties (Morey, 2007) and demonstrated adequate internal consistency in this sample (α = .75 to .90). Data Analysis Data analyses were conducted using a 3-step approach to latent class estimation and evaluation of the relationship between class membership and external correlates. As described by Asparouhov and Muth´en (2013), in the first step the latent class model is estimated using only latent class indicators. Then, most likely class membership is calculated using the latent class posterior distribution estimated in the first step, taking into account the rate of classification uncertainty. Last, most likely class membership is used to examine class differences on external correlates not included in the latent model. The statistical significance of conditional class specific mean
differences was evaluated by calculating Wald tests of mean equality, which can be used for both binary and continuous variables. We specified external correlates as continuous distal outcomes with unequal means and variances in each class. A recent simulation study demonstrated superiority of the 3-step approach over other similar methods (Asparouhov & Muth´en, 2013). PCL-S and MDI depersonalization and derealization items were submitted to LPA using the Mplus Version 7 (Muth´en & Muth´en, 1998–2012) mixture modeling procedure, with the robust maximum likelihood (MLR) estimator. Missing data were addressed using full information maximum likelihood (FIML), and acceptable covariance coverage was found (98.0% to 99.8% for latent class indicators, 36.0% to 98.0% for external correlates; Enders & Bandalos, 2001). FIML outperforms alternative methods for handling missing data across simulation studies, particularly when data are not missing completely at random and missing data rates are high (Enders, 2010). Based on previous LPA studies examining the dissociative subtype, a 3-class model was specified and compared to 2-, 4-, 5-, and 6-class models. First, models were examined with regard to overall quality and adequate convergence. Then, models were compared using a set of fit indices: (a) Bayesian information criterion (BIC; McLachlan & Peel, 2000), with lower values indicating better fit; (b) the Vuong-Lo-Mendell-Rubin adjusted likelihood ratio test (LRT-A; Lo, Mendell & Rubin, 2001); and (c) the bootstrapped likelihood ratio test (BLRT; Nylund, Asparouhov, & Muth´en, 2007), with significant p values suggesting the specified model provides better fit compared to a model with one fewer class. In addition, models were compared on entropy (Muth´en, 2004), with values closer to 1.0 indicating better classification quality, profile uniqueness, and theoretical considerations. Last, classes from the best-fitting model were compared on external correlates. Overall tests of
Table 2 Fit Indices for Competing Latent Class Models Model
Log-likelihood
BIC
Entropy
LMR-A p
BLRT p
2 Class 3 Class 4 Class
−19,419.23 −18,677.96 −18,226.11
39,354.52 38,048.20 37,320.71
.96 .96 .97
