20241111 - remove https

book.bib

@@ -111171,7 +111171,7 @@ @Article{Evans2023
   title    = {Emotion regulation as central to psychopathology across childhood and adolescence: a commentary on {N}obakht et al. (2023)},
   year     = {in press},
   abstract = {An important goal of clinical/developmental research is to identify factors contributing to the onset and maintenance of psychopathology – particularly factors that could be modified through intervention. Large-scale, multi-informant, longitudinal studies provide valuable opportunities for testing such etiological hypotheses, as illustrated by Nobakht et al.'s recent six-wave cohort study spanning ages 4–14. At a within-person level, emotion regulation (ER) deficits consistently predicted oppositional defiant disorder (ODD) symptoms (including both irritability and defiance), whereas victimization did not. These results comport with growing evidence highlighting ER's centrality to ODD and psychopathology more broadly. While the ER findings carry promising implications, caution is warranted in interpreting the results for victimization given that its association with psychopathology is well-documented. More research is needed to test precise questions about within- and between-person processes involving ER, victimization, and psychopathology across development. Pressing research questions include whether, how, and when youths' ER can be modified, and with what effects on clinical outcomes.},
-  doi      = {https://doi.org/10.1111/jcpp.13910},
+  doi      = {10.1111/jcpp.13910},
   url      = {https://acamh.onlinelibrary.wiley.com/doi/abs/10.1111/jcpp.13910},
 }
 
@@ -111198,7 +111198,7 @@ @Article{Yu2023
   pages    = {348--357},
   volume   = {16},
   abstract = {Abstract Structural equation modeling (SEM) plays an important role in business and social science and so do composites, that is, linear combinations of variables. However, existing approaches to integrate composites into structural equation models still have limitations. A major leap forward has been the Henseler–Ogasawara (H–O) specification, which for the first time allows for seamlessly integrating composites into structural equation models. In doing so, it relies on emergent variables, that is, the composite of interest, and one or more orthogonal excrescent variables, that is, composites that have no surplus meaning but just span the remaining space of the emergent variable's components. Although the H–O specification enables researchers to flexibly model composites in SEM, it comes along with several practical problems: (i) The H–O specification is difficult to visualize graphically; (ii) its complexity could create difficulties for analysts, and (iii) at times SEM software packages seem to encounter convergence issues with it. In this paper, we present a refinement of the original H–O specification that addresses these three problems. In this new specification, only two components load on each excrescent variable, whereas the excrescent variables are allowed to covary among themselves. This results in a simpler graphical visualization. Additionally, researchers facing convergence issues of the original H–O specification are provided with an alternative specification. Finally, we illustrate the new specification's application by means of an empirical example and provide guidance on how (standardized) weights including their standard errors can be calculated in the R package lavaan. The corresponding Mplus model syntax is provided in the Supplementary Material.},
-  doi      = {https://doi.org/10.1002/sam.11608},
+  doi      = {10.1002/sam.11608},
   url      = {https://onlinelibrary.wiley.com/doi/abs/10.1002/sam.11608},
 }
 
@@ -111356,7 +111356,7 @@ @Article{Shiffman2008
   pages    = {1--32},
   volume   = {4},
   abstract = {Assessment in clinical psychology typically relies on global retrospective self-reports collected at research or clinic visits, which are limited by recall bias and are not well suited to address how behavior changes over time and across contexts. Ecological momentary assessment (EMA) involves repeated sampling of subjects’ current behaviors and experiences in real time, in subjects’ natural environments. EMA aims to minimize recall bias, maximize ecological validity, and allow study of microprocesses that influence behavior in real-world contexts. EMA studies assess particular events in subjects’ lives or assess subjects at periodic intervals, often by random time sampling, using technologies ranging from written diaries and telephones to electronic diaries and physiological sensors. We discuss the rationale for EMA, EMA designs, methodological and practical issues, and comparisons of EMA and recall data. EMA holds unique promise to advance the science and practice of clinical psychology by shedding light on the dynamics of behavior in real-world settings.},
-  doi      = {https://doi.org/10.1146/annurev.clinpsy.3.022806.091415},
+  doi      = {10.1146/annurev.clinpsy.3.022806.091415},
   keywords = {experience sampling real-time data capture diary},
   url      = {https://www.annualreviews.org/content/journals/10.1146/annurev.clinpsy.3.022806.091415},
 }
@@ -111369,7 +111369,7 @@ @Article{Trull2013
   pages    = {151--176},
   volume   = {9},
   abstract = {Ambulatory assessment (AA) covers a wide range of assessment methods to study people in their natural environment, including self-report, observational, and biological/physiological/behavioral. AA methods minimize retrospective biases while gathering ecologically valid data from patients\' everyday life in real time or near real time. Here, we report on the major characteristics of AA, and we provide examples of applications of AA in clinical psychology (a) to investigate mechanisms and dynamics of symptoms, (b) to predict the future recurrence or onset of symptoms, (c) to monitor treatment effects, (d) to predict treatment success, (e) to prevent relapse, and (f) as interventions. In addition, we present and discuss the most pressing and compelling future AA applications: technological developments (the smartphone), improved ecological validity of laboratory results by combined lab-field studies, and investigating gene-environment interactions. We conclude with a discussion of acceptability, compliance, privacy, and ethical issues.},
-  doi      = {https://doi.org/10.1146/annurev-clinpsy-050212-185510},
+  doi      = {10.1146/annurev-clinpsy-050212-185510},
   keywords = {behavior observation smartphone ecological validity e-diary psychophysiological monitoring},
   url      = {https://www.annualreviews.org/content/journals/10.1146/annurev-clinpsy-050212-185510},
 }
@@ -111532,7 +111532,7 @@ @Article{Kline2024
   pages    = {1293--1306},
   volume   = {59},
   abstract = {Consistent with reporting standards for structural equation modelling (SEM), model fit should be evaluated at two different levels, global and local. Global fit concerns the overall or average correspondence between the entire data matrix and the model, given the parameter estimates for the model. Local fit is evaluated at the level of the residuals, or differences between observed and predicted associations for every pair of measured variables in the model. It can happen that models with apparently satisfactory global fit can nevertheless have problematic local fit. This may be especially true for relatively large models with many variables, where serious misspecification is indicated by some larger residuals, but their contribution to global fit is diluted when averaged together with all the other smaller residuals. It can be challenging to evaluate local fit in large models with dozens or even hundreds of variables and corresponding residuals. Thus, the main goal of this tutorial is to offer suggestions about how to efficiently evaluate and describe local fit for large structural equation models. An empirical example is described where all data, syntax and output files are freely available to readers.},
-  doi      = {https://doi.org/10.1002/ijop.13252},
+  doi      = {10.1002/ijop.13252},
   url      = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ijop.13252},
 }