Return to work and psychosocial trajectories after breast cancer: a longitudinal and sequential approach.

PURPOSE: We aimed to describe the psychosocial adjustments according to return to work (RTW) trajectories in breast cancer survivors (BCS) using a sequential and temporal approach. METHODS: We used BCS data included from February 2015 to April 2016 in the Longitudinal Study on Behavioural, Economic and Sociological Changes after Cancer (ELCCA) cohort. RTW trajectories were identified using the sequence analysis method followed by a clustering. Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale and the EORTC quality of life questionnaire was used at inclusion and all follow-up visits to assess Health-Related Quality of Life (HRQoL). RESULTS: Fifty-two BCS were included in the study among whom four clusters of RTW trajectories were identified and labeled: slow RTW (N = 10), quick RTW (N = 27), partial RTW (N = 8), and part-time work (N = 7). Quick and slow RTW clusters showed slightly lower baseline mean levels of anxiety and higher levels of HRQoL. In the 4 years following diagnosis, BCS in the quick RTW cluster tended to report higher HRQoL in terms of functioning and less symptoms of pain and fatigue while those in the partial RTW cluster showed a lower HRQoL on almost all dimensions. All clusters showed an increase in pain and fatigue symptoms until 6 months followed by a tendency to recover baseline levels. CONCLUSIONS: The results of this study suggest that BCS who return to full-time work (slow and quick RTW patterns) recover better than patients who return to part-time work (partial and part-time RTW patterns).

Performance of a Rasch-based method for group comparisons of longitudinal change and response shift at the item level in PRO data: A simulation study.

The growing interest in patient perception and experience in healthcare has led to an increase in the use of patient-reported outcomes (PRO) data. However, chronically ill patients may regularly adapt to their disease and, as a consequence, might change their perception of the PRO being measured. This phenomenon named response shift (RS) may occur differently depending on clinical and individual characteristics. The RespOnse Shift ALgorithm at the Item level (ROSALI), a method for RS analysis at the item level based on Rasch models, has recently been extended to explore heterogeneity of item-level RS between two groups of patients. The performances of ROSALI in terms of RS detection at the item level and biases of estimated differences in latent variable means were assessed. A simulation study was performed to investigate four scenarios: no RS, RS in only one group, RS affecting both groups either in a similar or a different way. Performances of ROSALI were assessed using rates of false detection of RS when no RS was simulated and a set of criteria (presence of RS, correct identification of items and groups affected by RS) when RS was simulated. Rates of false detection of RS were low indicating that ROSALI satisfactorily prevents from mistakenly inferring RS. ROSALI is able to detect RS and identify the item and group(s) affected when RS affects all response categories of an item in the same way. The performances of ROSALI depend mainly on the sample size and the degree of heterogeneity of item-level RS.

Modeling repeated self-reported outcome data: A continuous-time longitudinal Item Response Theory model.

Item Response Theory (IRT) models have received growing interest in health science for analyzing latent constructs such as depression, anxiety, quality of life or cognitive functioning from the information provided by each individual's items responses. However, in the presence of repeated item measures, IRT methods usually assume that the measurement occasions are made at the exact same time for all patients. In this paper, we show how the IRT methodology can be combined with the mixed model theory to provide a longitudinal IRT model which exploits the information of a measurement scale provided at the item level while simultaneously handling observation times that may vary across individuals and items. The latent construct is a latent process defined in continuous time that is linked to the observed item responses through a measurement model at each individual- and occasion-specific observation time; we focus here on a Graded Response Model for binary and ordinal items. The Maximum Likelihood Estimation procedure of the model is available in the R package lcmm. The proposed approach is contextualized in a clinical example in end-stage renal disease, the PREDIALA study. The objective is to study the trajectories of depressive symptomatology (as measured by 7 items of the Hospital Anxiety and Depression scale) according to the time from registration on the renal transplant waiting list and the renal replacement therapy. We also illustrate how the method can be used to assess Differential Item Functioning and lack of measurement invariance over time.

Does Differential Item Functioning Jeopardize the Comparability of Health-Related Quality of Life Assessment Between Patients and Proxies in Patients with Moderate-to-Severe Traumatic Brain Injury?

BACKGROUND: Health-related quality of life (HRQoL) is clearly recognized as a patient-important outcome in patients with traumatic brain injury (TBI). Patient-reported outcomes are therefore often used and supposed to be directly reported by the patients without interpretation of their responses by a physician or anyone else. However, patients with TBI are often unable to self-report because of physical and/or cognitive impairments. Thus, proxy-reported measures, e.g., family members, are often used on the patient's behalf. Yet, many studies have reported that proxy and patient ratings differ and are noncomparable. However, most studies usually do not account for other potential confounding factors that may be associated with HRQoL. In addition, patients and proxies can interpret some items of the patient-reported outcomes differently. As a result, item responses may not only reflect patients' HRQoL but also the respondent's (patient or proxy) own perception of the items. This phenomenon, called differential item functioning (DIF), can lead to substantial differences between patient-reported and proxy-reported measures and compromise their comparability, leading to highly biased HRQoL estimates. Using data from the prospective multicenter continuous hyperosmolar therapy in traumatic brain-injured patients study (240 patients with HRQoL measured with the Short Form-36 (SF-36)), we assessed the comparability of patients' and proxies' reports by evaluating the extent to which items perception differs (i.e., DIF) between patients and proxies after controlling for potential confounders. METHODS: Items at risk of DIF adjusting for confounders were examined on the items of the role physical and role emotional domains of the SF-36. RESULTS: Differential item functioning was evidenced in three out of the four items of the role physical domain measuring role limitations due to physical health problems and in one out of the three items of the role emotional domain measuring role limitations due to personal or emotional problems. Overall, despite an expected similar level of role limitations between patients who were able to respond and those for whom proxies responded, proxies tend to give more pessimistic responses than patients in the case of major role limitations and more optimistic responses than patients in the case of minor limitations. CONCLUSIONS: Patients with moderate-to-severe TBI and proxies seem to have different perceptions of the items measuring role limitations due to physical or emotional problems, questioning the comparability of patient and proxy data. Therefore, aggregating proxy and patient responses may bias HRQoL estimates and alter medical decision-making based on these patient-important outcomes.

Posttraumatic growth inventory: challenges with its validation among French cancer patients.

BACKGROUND: The Posttraumatic growth inventory (PTGI) aims to assess the positive psychological changes that individuals can perceive after a traumatic life event such as a cancer diagnosis. Several French translations of the PTGI have been proposed, but comprehensive data on their psychometric properties are lacking. This study aimed to provide a more complete assessment of the psychometric properties of one of the most used PTGI translations in early-stage breast cancer and melanoma patients. METHODS: A sample of 379 patients completed the PTGI two years after their cancer diagnosis. A confirmatory analysis was first performed to determine whether the initial five-factor structure of the PTGI was adequate for this French version. As issues were identified in the translation and in the questionnaire structure, we performed an exploratory analysis to determine the most suitable structure for this questionnaire. Validity and reliability of the evidenced structured were then assessed. RESULTS: The exploratory analysis evidenced a four-factor structure close to the initial structure: four of the five initial domains were recovered, and items from the unrecovered domain were split into the other domains. This new structure showed good internal consistency and acceptable validity. CONCLUSIONS: This study highlights that the process of translation and cross-cultural validation of questionnaires is crucial to obtain valid and reliable psychometric instruments. We advise French psycho-oncology researchers and psychotherapists to (i) use the revised translation of Lelorain et al. (2010) proposed in this manuscript and (ii) use the four scores newly evidenced with a grouping of two response categories.

Evaluation of the link between the Guttman errors and response shift at the individual level.

PURPOSE: Methods for response shift (RS) detection at the individual level could be of great interest when analyzing changes in patient-reported outcome data. Guttman errors (GEs), which measure discrepancies in respondents' answers compared to the average sample responses, might be useful for detecting RS at the individual level between two time points, as RS may induce an increase in the number of discrepancies over time. This study aims to establish the link between recalibration RS and the change in the number of GEs over time (denoted index [Formula: see text]) via simulations and explores the discriminating ability of this index. METHODS: We simulated the responses of individuals affected or not affected by recalibration RS (defined as changes in the patients' standard of measurement) to determine whether simulated individuals with recalibration had a greater change in the number of GEs over time than individuals without recalibration. The effects of factors related to the sample, the questionnaire structure and recalibration were investigated. As an illustrative example, the change in the number of GEs was computed in patients suffering from eating disorders. RESULTS: Within simulations, simulated individuals affected by recalibration had, on average, a greater change in the number of GEs over time than did individuals without RS. Some of the parameters related to the questionnaire structure and recalibration magnitude appeared to have substantial effects on the values of [Formula: see text]. Discriminating abilities appeared, however, globally low. CONCLUSION: Some evidence of the link between recalibration and the change in GEs was found in this study. GEs could be a valuable nonparametric tool for RS detection at a more individual level, but further investigation is needed.

Investigation of measurement invariance in longitudinal health-related quality of life in preemptive or previously dialyzed kidney transplant recipients.

PURPOSE: Kidney transplantation (KT) can impact patients' evaluation of health-related quality of life (HRQoL) as they adapt to their new life with a graft and its changes. Patients may adapt to KT in a different way, depending on whether they were on dialysis prior to transplantation or not (i.e. preemptive group). This may result in lack of measurement invariance between these patients' groups and/or over time (i.e. response shift, RS) which may invalidate the between-group comparison of HRQoL change scores. The aim of this study was to investigate and compare RS before and after KT between these two patients' groups. Measurement invariance was investigated between groups and over time with three measurement occasions. METHODS: Adult patients completed the SF-36 at the last visit before KT, and 3, 6 months after. A structural equation model-based procedure was used to (i) detect and take into account measurement non-invariance between groups and RS, if appropriate, (ii) identify the period of occurrence of RS, (iii) study the heterogeneity of RS between the two groups. RESULTS: Before KT (i.e. baseline), measurement invariance was not rejected between dialyzed (n = 196) and preemptive (n = 178) patients' groups. Between baseline and 3 months after KT, similar uniform recalibration was detected on the general health domain in both groups. Uniform recalibration was found between 3- and 6 months after KT on the vitality domain for preemptive patients only. CONCLUSION: HRQoL, adjusted for RS, increased overall for preemptive and dialyzed kidney transplant patients after transplantation. RS may reflect differing adaptation processes following KT.

The minimal perceived change: a formal model of the responder definition according to the patient's meaning of change for patient-reported outcome data analysis and interpretation.

BACKGROUND: Patient-Reported Outcomes (PROs) are standardized questionnaires used to measure subjective outcomes such as quality of life in healthcare. They are considered paramount to assess the results of therapeutic interventions. However, because their calibration is relative to internal standards in people's mind, changes in PRO scores are difficult to interpret. Knowing the smallest value in the score that the patient perceives as change can help. An estimator linking the answers to a Patient Global Rating of Change (PGRC: a question measuring the overall feeling of change) with change in PRO scores is frequently used to obtain this value. In the last 30 years, a plethora of methods have been used to obtain these estimates, but there is no consensus on the appropriate method and no formal definition of this value. METHODS: We propose a model to explain changes in PRO scores and PGRC answers. RESULTS: A PGRC measures a construct called the Perceived Change (PC), whose determinants are elicited. Answering a PGRC requires discretizing a continuous PC into a category using threshold values that are random variables. Therefore, the populational value of the Minimal Perceived Change (MPC) is the location parameter value of the threshold on the PC continuum defining the switch from the absence of change to change. CONCLUSIONS: We show how this model can help to hypothesize what are the appropriate methods to estimate the MPC and its potential to be a rigorous theoretical basis for future work on the interpretation of change in PRO scores.

Longitudinal associations between coping strategies, locus of control and health-related quality of life in patients with breast cancer or melanoma.

PURPOSE: A diagnosis of breast cancer or melanoma is a traumatic life event that patients have to face. However, their locus-of-control (LOC) beliefs and coping strategies as well as the associations with health-related quality of life (HRQoL) changes over time are still not well known and rarely compared by cancer site. METHODS: The objective of this longitudinal study was to assess the association of LOC (Cancer Locus-of-Control Scale) and coping (Brief Cope) changes, with change in HRQoL (EORTC QLQ-C30) over time in newly diagnosed breast cancer and melanoma patients at 1, 6, 12, and 24 month post-diagnosis. Mixed models were used to compare LOC and coping longitudinal changes as well as their associations with HRQoL changes in early-stage breast cancer and melanoma patients. RESULTS: Overall, 215 breast cancer and 78 melanoma patients participated in the study. At baseline, HRQoL levels were often higher for breast cancer compared to melanoma patients. For breast cancer and melanoma patients, negative coping strategies and perceived control over the course of illness were negatively and positively associated with HRQoL changes, respectively. For breast cancer patients only, emotional coping and internal causal attribution were negatively associated with HRQoL changes. For both cancer sites, living with a partner correlated with worse HRQoL. CONCLUSIONS: Understanding coping strategies and LOC beliefs used by patients soon after their cancer diagnosis and over the course of illness can help identifying psychological and supportive care to modify maladaptive thoughts and beliefs and promote more adaptive behaviors to ultimately improve patients' well-being and HRQoL.

Comparison of longitudinal quality of life outcomes in preemptive and dialyzed patients on waiting list for kidney transplantation.

PURPOSE: The waiting list period for kidney transplantation can be lengthy and associated with a deteriorated health-related quality of life (HRQoL). It might also be experienced differently depending on the experience of renal replacement therapy (preemptive or dialyzed patients), and the type of dialysis. The main objective of this study is to measure and compare HRQoL changes in preemptive, hemodialysis (HD), and peritoneal dialysis (PD) patients during the waiting list period for kidney transplantation. METHODS: A sample of adult patients on kidney transplant waiting list from three French University Hospital centers was recruited. HRQoL was measured using the SF-36 and a specific questionnaire (ReTransQol), which were collected every 6 months before transplantation in preemptive, HD, and PD patients. Mixed-effects models taking into account time and possible confounding factors were used to compare HRQoL changes between the three groups. RESULTS: Preemptive (n = 230), HD (n = 177), and PD patients (n = 39) were enrolled. The renal replacement therapy modalities, time (time on waiting list and age at registration), and gender were associated with HRQoL changes. The HD and PD patients had a significantly lower perceived HRQoL on Role Physical, Social Functioning, and Role Emotional dimensions than the preemptive patients, with lower scores for PD compared to HD patients. The HRQoL scores of all patients were lower compared to the French general population for all dimensions. CONCLUSIONS: A better understanding of pre-transplantation patients' experience can help improving patient care with adapted educational programs and psychological support depending on the type of renal replacement therapy.

A systematic review of dimensions evaluating patient experience in chronic illness.

BACKGROUND: Living with a chronic disease often means experiencing chronic treatments and regular multidisciplinary monitoring as well as a profound life-changing experience which may impact all aspects of a patients life. The patient experience of chronic disease is frequently assessed by patient reported measures (PRMs) which incorporate patients perspectives to better understand how illness, treatment and care impact the entirety of a patient's life. The purpose of this review was to collect and review different kinds of available PRM instruments validated for chronic patients, to produce an inventory of explored concepts in these questionnaires and to identify and classify all dimensions assessing chronic patients experience. METHODS: A systematic review of PRM instruments validated for chronic patients was conducted from three databases (Medline, the Cochrane library, and Psycinfo). Articles were selected after a double reading and questionnaires were classified according to their targeted concept. Then, all dimensions of the questionnaires were clustered into different categories. RESULTS: 107 primary validation studies of PRM questionnaires were selected. Five kinds of instruments were recorded: 1) Questionnaires assessing health related quality of life or quality of life; 2) Instruments focusing on symptoms and functional status; 3) Instruments exploring patients' feelings and attitude about illness; 4) Questionnaires related to patients' experience of treatment or healthcare; 5) Instruments assessing patients attitudes about treatment or healthcare. Twelve categories of dimensions were obtained from these instruments. CONCLUSIONS: This review provided an overview of some of the dimensions used to explore chronic patient experience. A large PRM diversity exists and none of the reviewed and selected questionnaires covered all identified categories of dimensions of patient experience of chronic disease. Furthermore, the definition of explored concepts varies widely among researchers and complex concepts often lack a clear definition in the reviewed articles. Before attempting to measure chronic patient experience, researchers should construct appropriate instruments focusing on well-defined concepts and dimensions encompassing patient's personal experience, attitude and adaptation to illness, treatment or healthcare.

The Guttman errors as a tool for response shift detection at subgroup and item levels.

PURPOSE: Statistical methods for identifying response shift (RS) at the individual level could be of great practical value in interpreting change in PRO data. Guttman errors (GE) may help to identify discrepancies in respondent's answers to items compared to an expected response pattern and to identify subgroups of patients that are more likely to present response shift. This study explores the benefits of using a GE-based method for RS detection at the subgroup and item levels. METHODS: The analysis was performed on the SatisQoL study. The number of GE was determined for each individual at each time of measurement (at baseline T0 and 6 months after discharge M6). Individuals showing discrepancies (with many GE) were suspected to interpret the items differently from the majority of the sample. Patients having a large number of GE at M6 only and not at T0 were assumed to present RS. Patients having a small number of GE at T0 and M6 were assumed to present no RS. The RespOnse Shift ALgorithm in Item response theory (ROSALI) was then applied on the whole sample and on both groups. RESULTS: Different types of RS (non-uniform recalibration, reprioritization) were more prevalent in the group composed of patients assumed to present RS based on GE. On the opposite, no RS was detected on patients having few GE. CONCLUSIONS: Guttman errors and item response theory models seem to be relevant tools to discriminate individuals affected by RS from the others at the item level.

Power and sample size determination for group comparison of patient-reported outcomes using polytomous Rasch models.

The analysis of patient-reported outcomes or other psychological traits can be realized using the Rasch measurement model. When the objective of a study is to compare groups of individuals, it is important, before the study, to define a sample size such that the group comparison test will attain a given power. The Raschpower procedure (RP) allows doing so with dichotomous items. The RP is extended to polytomous items. Several computational issues were identified, and adaptations have been proposed. The performance of this new version of RP is assessed using simulations. This adaptation of RP allows obtaining a good estimate of the expected power of a test to compare groups of patients in a large number of practical situations. A Stata module, as well as its implementation online, is proposed to perform the RP. Two versions of the RP for polytomous items are proposed (deterministic and stochastic versions). These two versions produce similar results in all of the tested cases. We recommend the use of the deterministic version, when the measure is obtained using small questionnaires or items with a few number of response categories, and the stochastic version elsewhere, so as to optimize computing time.

Power and sample size determination for the group comparison of patient-reported outcomes using the Rasch model: impact of a misspecification of the parameters.

BACKGROUND: Patient-reported outcomes (PRO) are important as endpoints in clinical trials and epidemiological studies. Guidelines for the development of PRO instruments and analysis of PRO data have emphasized the need to report methods used for sample size planning. The Raschpower procedure has been proposed for sample size and power determination for the comparison of PROs in cross-sectional studies comparing two groups of patients when an item reponse model, the Rasch model, is intended to be used for analysis. The power determination of the test of the group effect using Raschpower requires several parameters to be fixed at the planning stage including the item parameters and the variance of the latent variable. Wrong choices regarding these parameters can impact the expected power and the planned sample size to a greater or lesser extent depending on the magnitude of the erroneous assumptions. METHODS: The impact of a misspecification of the variance of the latent variable or of the item parameters on the determination of the power using the Raschpower procedure was investigated through the comparison of the estimations of the power in different situations. RESULTS: The power of the test of the group effect estimated with Raschpower remains stable or shows a very little decrease whatever the values of the item parameters. For most of the cases, the estimated power decreases when the variance of the latent trait increases. As a consequence, an underestimation of this variance will lead to an overestimation of the power of the group effect. CONCLUSION: A misspecification of the item difficulties regarding their overall pattern or their dispersion seems to have no or very little impact on the power of the test of the group effect. In contrast, a misspecification of the variance of the latent variable can have a strong impact as an underestimation of the variance will lead in some cases to an overestimation of the power at the design stage and may result in an underpowered study.

Validation of the French translation-adaptation of the impact of cancer questionnaire version 2 (IOCv2) in a breast cancer survivor population.

BACKGROUND: The Impact of Cancer version 2 (IOCv2) was designed to assess the physical and psychosocial health experience of cancer survivors through its positive and negative impacts. Although the IOCv2 is available in English and Dutch, it has not yet been validated for use in French-speaking populations. The current study was undertaken to provide a comprehensive assessment of the reliability and validity of the French language version of the IOCv2 in a sample of breast cancer survivors. METHODS: An adapted French version of the IOCv2 as well as demographic and medical information were completed by 243 women to validate the factor structure divergent/divergent validities and reliability. Concurrent validity was assessed by correlating the IOCv2 scales with measures from the SF-12, PostTraumatic Growth Inventory and Fear of Cancer Recurrence Inventory. RESULTS: The French version of the IOCv2 supports the structure of the original version, with four positive impact dimensions and four negative impact dimensions. This result was suggested by the good fit of the confirmatory factor analysis and the adequate reliability revealed by Cronbach's alpha coefficients and other psychometric indices. The concurrent validity analysis revealed patterns of association between IOCv2 scale scores and other measures. Unlike the original version, a structure with a Positive Impact domain consisting in the IOCv2 positive dimensions and a Negative Impact domain consisting in the negative ones has not been clearly evidenced in this study. The limited practical use of the conditional dimensions Employment Concerns and Relationship Concerns, whether the patient is partnered or not, did not make possible to provide evidence of validity and reliability of these dimensions as the subsets of sample to work with were not large enough. The scores of these conditional dimensions have to be used with full knowledge of the facts of this limitation of the study. CONCLUSIONS: Integrating IOCv2 into studies will contribute to evaluate the psychosocial health experience of the growing population of cancer survivors, enabling better understanding of the multi-dimensional impact of cancer.

Overall performance of Oort's procedure for response shift detection at item level: a pilot simulation study.

OBJECTIVE: This simulation study was designed to provide data on the performance of Oort's procedure (OP) for response shift (RS) detection (regarding type I error, power, and overall performance), according to sample characteristics, at item level. A specific objective was to assess the impact of using different information criteria (IC), as alternatives to the LRT (likelihood-ratio test), for global assessment of RS occurrence. METHODS: Responses to five binary items at two times of measurement were simulated. Thirty-six combinations of sample characteristics [sample size (n), "true change," correlations between the two latent variables and presence/absence of uniform recalibration RS (ur)] were considered. A thousand datasets were generated for each combination. RS detection was performed on each dataset following OP. Type I error and power of the global assessment of RS occurrence, as well as overall performance of the OP, were assessed. RESULTS: The estimated type I error was close to 5 % for the LRT and lower than 5 % for the IC. The estimated power was higher for the LRT as compared to the AIC, which was the highest among the other IC. For the LRT, the estimated power for n = 100 and for the combination of n = 200 and ur = 1 item was below 80 %. Otherwise, for other combinations of sample characteristics, the estimated power was above 90 %. CONCLUSION: For the LRT, higher values of power were estimated compared to IC with appropriate values of type I error. These results were consistent with Oort's proposal to use the LRT as the criterion to assess global RS occurrence.

RespOnse Shift ALgorithm in Item response theory (ROSALI) for response shift detection with missing data in longitudinal patient-reported outcome studies.

PURPOSE: Some IRT models have the advantage of being robust to missing data and thus can be used with complete data as well as different patterns of missing data (informative or not). The purpose of this paper was to develop an algorithm for response shift (RS) detection using IRT models allowing for non-uniform and uniform recalibration, reprioritization RS recognition and true change estimation with these forms of RS taken into consideration if appropriate. METHODS: The algorithm is described, and its implementation is shown and compared to Oort's structural equation modeling (SEM) procedure using data from a clinical study assessing health-related quality of life in 669 hospitalized patients with chronic conditions. RESULTS: The results were quite different for the two methods. Both showed that some items of the SF-36 General Health subscale were affected by response shift, but those items usually differed between IRT and SEM. The IRT algorithm found evidence of small recalibration and reprioritization effects, whereas SEM mostly found evidence of small recalibration effects. CONCLUSION: An algorithm has been developed for response shift analyses using IRT models and allows the investigation of non-uniform and uniform recalibration as well as reprioritization. Differences in RS detection between IRT and SEM may be due to differences between the two methods in handling missing data. However, one cannot conclude on the differences between IRT and SEM based on a single application on a dataset since the underlying truth is unknown. A next step would be to implement a simulation study to investigate those differences.

Assessment of score- and Rasch-based methods for group comparison of longitudinal patient-reported outcomes with intermittent missing data (informative and non-informative).

PURPOSE: The purpose of this study was to identify the most adequate strategy for group comparison of longitudinal patient-reported outcomes in the presence of possibly informative intermittent missing data. Models coming from classical test theory (CTT) and item response theory (IRT) were compared. METHODS: Two groups of patients' responses to dichotomous items with three times of assessment were simulated. Different cases were considered: presence or absence of a group effect and/or a time effect, a total of 100 or 200 patients, 4 or 7 items and two different values for the correlation coefficient of the latent trait between two consecutive times (0.4 or 0.9). Cases including informative and non-informative intermittent missing data were compared at different rates (15, 30 %). These simulated data were analyzed with CTT using score and mixed model (SM) and with IRT using longitudinal Rasch mixed model (LRM). The type I error, the power and the bias of the group effect estimations were compared between the two methods. RESULTS: This study showed that LRM performs better than SM. When the rate of missing data rose to 30 %, estimations were biased with SM mainly for informative missing data. Otherwise, LRM and SM methods were comparable concerning biases. However, regardless of the rate of intermittent missing data, power of LRM was higher compared to power of SM. CONCLUSIONS: In conclusion, LRM should be favored when the rate of missing data is higher than 15 %. For other cases, SM and LRM provide similar results.

Estimation of Parameters of the Rasch Model and Comparison of Groups in Presence of Locally Dependent Items.

Measurement specialists routinely assume examinee responses to test are independent of one another. However, previous research has shown that many tests contain item dependencies, and not accounting for these dependencies leads to misleading estimates of item and person parameters. In this paper, the marginal maximum likelihood estimation in Rasch model with the violation of the local independence is studied. The power of the Wald test on a group effect parameter on the latent traits in cross-sectional studies is examined under the local independence and the local item dependence assumptions. The different results are illustrated with simulation studies.