This study aims to conduct an in-depth analysis of social media data using causal inference methods to explore the underlying mechanisms driving user behavior patterns.By leveraging large-scale social media datasets,t...This study aims to conduct an in-depth analysis of social media data using causal inference methods to explore the underlying mechanisms driving user behavior patterns.By leveraging large-scale social media datasets,this research develops a systematic analytical framework that integrates techniques such as propensity score matching,regression analysis,and regression discontinuity design to identify the causal effects of content characteristics,user attributes,and social network structures on user interactions,including clicks,shares,comments,and likes.The empirical findings indicate that factors such as sentiment,topical relevance,and network centrality have significant causal impacts on user behavior,with notable differences observed among various user groups.This study not only enriches the theoretical understanding of social media data analysis but also provides data-driven decision support and practical guidance for fields such as digital marketing,public opinion management,and digital governance.展开更多
In order to understand the travel characteristics and behavior patterns of women in Wangjing area and explore whether the existing situation can meet women's needs for the use of street space,the area around Wangj...In order to understand the travel characteristics and behavior patterns of women in Wangjing area and explore whether the existing situation can meet women's needs for the use of street space,the area around Wangjing South Station of Metro Line 14 was taken as an example for analysis and research.Wangjing area was classified to the following six use attributes:company enterprise,transportation hub,education and culture,residential area,municipal facilities,leisure and entertainment.The proportion of each use attribute was evaluated according to four levels:A 25%and above(including 25%),B 15%-25%,C 15%-5%,D 5%and below(including 5%).Finally,whether the plot had composite functions was judged,and the spatio-temporal laws and behavior patterns of surrounding women were analyzed from the perspectives of time and space.展开更多
This study takes Gannan Tibetan Autonomous Prefecture as the place of case study and tourists as research objects. From the perspectives of geographical distribution of source tourist markets, Tourist activity behavio...This study takes Gannan Tibetan Autonomous Prefecture as the place of case study and tourists as research objects. From the perspectives of geographical distribution of source tourist markets, Tourist activity behavioral and spatial patterns of Tourists, this study looks into the geographical structure of the source tourists and spatial patterns by geography. The analysis of 341 questionnaires on tourists shows that:(1) The tourism cycle of Gannan is in the development phase, competing with adjacent Aba, and greatly impacted by the substitution effect and shadow effect of Aba.(2) The spatial distribution of tourist sources is concentrated, indicating that Gannan is a regional tourism destination. The temporal distance of tourists is mainly concentrated within the 6-hour traffi c circle.(3) Gannan Tibetan Autonomous Prefecture has already become the composite tourist destination dominated by leisure vacation. The minority folkcustom and special landscape are the most attractive tourism resources. Due to the impact of man-land harmonious lifestyle in the tourist areas, the environmental attitude of tourists is improved, and the transportation and shopping are the most vulnerable links in tourism service in Gannan Tibetan Autonomous Prefecture.(4) The spatial behavior of tourists in Gannan is mainly of single-destination style(52%), Transit leg and circle tour style(7%) as well as circle tour style(41%). The spatial distribution of tourist fl ow in Gannan shows a signifi cant feature "more in the north, less in the south and dependent on National Road". Tourism resources, transport facilities, regional competition and lack of route connecting different ecological units are important causes of the spatial distribution of self-help tourists.展开更多
GPS positioning data are increasingly utilized in environmental behavior studies to explore the spatial-temporal behavioral patterns of individuals.However,individuals’stay behavioral pattern and its influencing fact...GPS positioning data are increasingly utilized in environmental behavior studies to explore the spatial-temporal behavioral patterns of individuals.However,individuals’stay behavioral pattern and its influencing factors,which are particularly significant for the design and management of scenic architectural complexes,have not been thoroughly examined.Using GPS trajectory data collected from the Palace Museum in Beijing(China),this paper investigated the visitors’stay behavior patterns associated with temporal,spatial,and environmental influencing factors.Types of stay behavior and characteristics of stay in main stay areas were automatically recognized using Python algorithms for further and quantitative analysis.Results showed that visitors’stay time exhibited a consistent pattern regarding psychological time allocation,a relatively unsignificant pattern regarding lunch hour,and no clear pattern regarding fatigue feature.Grouped regression analysis showed positive linear relationships with similar slopes between the average stay length and the number of stay occurrences in each type of stay area.Partial correlation analysis revealed the underlying connection between the impact of seats and greenery on stay behavior.Individually,each of the two environmental elements showed limited effect on stay frequency and stay length,while incorporating greenery into seating areas would notably increase both stay frequency and stay length.展开更多
In accounts of the development and progression of psychophysical disorders such as Hereditary Spastic Paraplegia (HSP) and Facioscapulohumeral Muscular Dystrophy (FSHD), the role of beliefs, perceptions, and behaviora...In accounts of the development and progression of psychophysical disorders such as Hereditary Spastic Paraplegia (HSP) and Facioscapulohumeral Muscular Dystrophy (FSHD), the role of beliefs, perceptions, and behavioral patterns has often been overlooked in favor of a genetically determinist paradigm. This paper explores the impact of NeuroPhysics Treatment (NPT) on patients with HSP and FSHD. Through a series of clinical case reports, I demonstrate how intensive four-day NPT sessions can lead to rapid restoration of lost functions, challenging the conventional view of these disorders. I hypothesize that, by modulating the patient’s perceptual and behavioral frameworks, NPT facilitates the emergence of healthier patterns, suggesting that environmental and psychological factors significantly influence the manifestation and management of these conditions. These findings indicate that the role of genetic inheritance may be overstated and that beliefs and perceptions could play a crucial role in the evolution of psychophysical disorders. The implications of this research extend beyond the traditional treatment paradigms, advocating for a more holistic approach that integrates the psychophysical dimensions of health and challenges the deterministic perspective of genetic inheritance.展开更多
Trajectory clustering and behavior pattern extraction are the foundations of research into activity perception of objects in motion. In this paper, a new framework is proposed to extract behavior patterns through traj...Trajectory clustering and behavior pattern extraction are the foundations of research into activity perception of objects in motion. In this paper, a new framework is proposed to extract behavior patterns through trajectory analysis. Firstly, we introduce directional trimmed mean distance （DTMD）, a novel method used to measure similarity between trajectories. DTMD has the attributes of anti-noise, self-adaptation and the capability to determine the direction for each trajectory. Secondly, we use a hierarchical clustering algorithm to cluster trajectories. We design a length-weighted linkage rule to enhance the accuracy of trajectory clustering and reduce problems associated with incomplete trajectories. Thirdly, the motion model parameters are estimated for each trajectory＇s classification, and behavior patterns for trajectories are extracted. Finally, the difference between normal and abnormal behaviors can be distinguished.展开更多
Trajectory data mining is widely used in military and civil applications,such as early warning and surveillance system,intelligent traffic system and so on.Through trajectory similarity measurement and clustering,targ...Trajectory data mining is widely used in military and civil applications,such as early warning and surveillance system,intelligent traffic system and so on.Through trajectory similarity measurement and clustering,target behavior patterns can be found from massive spatiotemporal trajectory data.In order to mine frequent behaviors of targets from complex historical trajectory data,a behavior pattern mining algorithm based on spatiotemporal trajectory multidimensional information fusion is proposed in this paper.Firstly,spatial–temporal Hausdorff distance is pro-posed to measure multidimensional information differences of spatiotemporal trajectories,which can distinguish the behaviors with similar location but different course and velocity.On this basis,by combining the idea of k-nearest neighbor and density peak clustering,a new trajectory clustering algorithm is proposed to mine behavior patterns from trajectory data with uneven density distribu-tion.Finally,we implement the proposed algorithm in simulated and radar measured trajectory data respectively.The experimental results show that the proposed algorithm can mine target behavior patterns from different complex application scenarios more quickly and accurately com-pared to the existing methods,which has a good application prospect in intelligent monitoring tasks.展开更多
This study examines the database search behaviors of individuals, focusing on gender differences and the impact of planning habits on information retrieval. Data were collected from a survey of 198 respondents, catego...This study examines the database search behaviors of individuals, focusing on gender differences and the impact of planning habits on information retrieval. Data were collected from a survey of 198 respondents, categorized by their discipline, schooling background, internet usage, and information retrieval preferences. Key findings indicate that females are more likely to plan their searches in advance and prefer structured methods of information retrieval, such as using library portals and leading university websites. Males, however, tend to use web search engines and self-archiving methods more frequently. This analysis provides valuable insights for educational institutions and libraries to optimize their resources and services based on user behavior patterns.展开更多
The present study has evaluated the effect of architectural forms on the walking activity of citizens as a behavioral model in urban physical spaces.The research hypothesis claims that by designing purposeful and appr...The present study has evaluated the effect of architectural forms on the walking activity of citizens as a behavioral model in urban physical spaces.The research hypothesis claims that by designing purposeful and appropriate architectural forms,the behavior and actions of users in urban physical spaces can be to some extent,it designed or controlled,and that the pattern and domains of human behavior in urban streets are the result of the components of environmental quality that are included in the design of that street.The present theoretical proposition has been tested in two sequences from Valiasr Street in Tehran.At the theoretical level,the research method is descriptive-analytical and at the experimental level,it is a survey that has been done using the behavioral research method.The results show that the floor form and street form are the most influential architectural forms in urban physical spaces on the activity of users walking from space in the study sample.Also,some environmental factors have a direct effect on human reactions;The research findings show that people’s speed is directly related to the dimensions of sidewalk carpets and a person tries to take a step according to the senses he receives from the sidewalk flooring form and as a result his speed changes according to those forms.展开更多
The prevalence of HIV in high risk population is influenced significantly the behavioral and sociodemographic characteristics. However, considering the complexity of behavior among female sex workers, the relationship...The prevalence of HIV in high risk population is influenced significantly the behavioral and sociodemographic characteristics. However, considering the complexity of behavior among female sex workers, the relationship between a particular behavioral pattern and the HIV status of this “at risk” population assumes significance. Data generated in a community-based cross-sectional study earlier carried out to assess the prevalence estimates, at district level, of HIV status in eight districts of State of Andhra Pradesh, India was used to carry out factor analysis to explore the role of demographic and behavioral pattern and their relationship with the HIV status among female sex workers. Data on 3083 female sex workers in the study revealed that there existed nine patterns among demographic and behavioral characteristics, which explained 62% of the total variation through factor analysis. Further, cluster analysis was performed to identify the groups of individuals having similar characteristics. Two of those clusters had sizeable numbers having similar characteristics. FSWs belonging to cluster 2 had significantly high risk factors compared with Cluster 1. The overall prevalence of HIV was 11.4% (10.6% in cluster 1 and 15.9% in cluster 2) among high risk population. There exists a strong relationship between behavioral patterns and HIV positive.展开更多
Selecting the optimal speed for dynamic obstacle avoidance in complex man–machine environments is a challenging problem for mobile robots inspecting hazardous gases.Consideration of personal space is important,especi...Selecting the optimal speed for dynamic obstacle avoidance in complex man–machine environments is a challenging problem for mobile robots inspecting hazardous gases.Consideration of personal space is important,especially in a relatively narrow man–machine dynamic environments such as warehouses and laboratories.In this study,human and robot behaviors in man–machine environments are analyzed,and a man–machine social force model is established to study the robot obstacle avoidance speed.Four typical man–machine behavior patterns are investigated to design the robot behavior strategy.Based on the social force model and man–machine behavior patterns,the fuzzy-PID trajectory tracking control method and the autonomous obstacle avoidance behavior strategy of the mobile robot in inspecting hazardous gases in a relatively narrow man–machine dynamic environment are proposed to determine the optimal robot speed for obstacle avoidance.The simulation analysis results show that compared with the traditional PID control method,the proposed controller has a position error of less than 0.098 m,an angle error of less than 0.088 rad,a smaller steady-state error,and a shorter convergence time.The crossing and encountering pattern experiment results show that the proposed behavior strategy ensures that the robot maintains a safe distance from humans while performing trajectory tracking.This research proposes a combination autonomous behavior strategy for mobile robots inspecting hazardous gases,ensuring that the robot maintains the optimal speed to achieve dynamic obstacle avoidance,reducing human anxiety and increasing comfort in a relatively narrow man–machine environment.展开更多
Process data recorded by computer-based assessments reflect how respondents solve problems and thus contain rich information about respondents as well as tasks.Considering that different respondents may exhibit differ...Process data recorded by computer-based assessments reflect how respondents solve problems and thus contain rich information about respondents as well as tasks.Considering that different respondents may exhibit different behavioral characteristics during problem-solving process,in this study,we propose a mixture one-parameter state response(Mix1P-SR)measurement model.This model assumes that respondents belong to discrete latent classes with different propensities towards responses to task states during the problem-solving process,and the varying response propensities are captured by different state parameters across classes.A Markov Chain Monte Carlo algorithm for the estimation of model parameters and classification of respondents is described.The simulation study shows that the Mix1P-SR model could recover parameters well on the premise that the average sequence length was not too short.Moreover,larger sample size,longer sequences,more uniform mixing proportions,and lower interclass similarity facilitated model convergence,model selection,and parameter estimation accuracy,with sequence length being particularly important.Based on the empirical data from PISA 2012,the Mix1P-SR model identified two latent classes of respondents.They had different patterns of state easiness parameters and exhibited different state response patterns,which affected their problem solving results.Implications for model application and future research directions are discussed.展开更多
文摘This study aims to conduct an in-depth analysis of social media data using causal inference methods to explore the underlying mechanisms driving user behavior patterns.By leveraging large-scale social media datasets,this research develops a systematic analytical framework that integrates techniques such as propensity score matching,regression analysis,and regression discontinuity design to identify the causal effects of content characteristics,user attributes,and social network structures on user interactions,including clicks,shares,comments,and likes.The empirical findings indicate that factors such as sentiment,topical relevance,and network centrality have significant causal impacts on user behavior,with notable differences observed among various user groups.This study not only enriches the theoretical understanding of social media data analysis but also provides data-driven decision support and practical guidance for fields such as digital marketing,public opinion management,and digital governance.
基金Sponsored by 2022 Beijing Undergraduate Innovation and Entrepreneurship Training PlanConstruction of Demonstration Off-campus Practice Base for Integration of Industry and Education+1 种基金Beijing Municipal Education Commission Social Science Project(KM202010009002)“Young Yu You Talents Training Plan”of North China University of Technology。
文摘In order to understand the travel characteristics and behavior patterns of women in Wangjing area and explore whether the existing situation can meet women's needs for the use of street space,the area around Wangjing South Station of Metro Line 14 was taken as an example for analysis and research.Wangjing area was classified to the following six use attributes:company enterprise,transportation hub,education and culture,residential area,municipal facilities,leisure and entertainment.The proportion of each use attribute was evaluated according to four levels:A 25%and above(including 25%),B 15%-25%,C 15%-5%,D 5%and below(including 5%).Finally,whether the plot had composite functions was judged,and the spatio-temporal laws and behavior patterns of surrounding women were analyzed from the perspectives of time and space.
文摘This study takes Gannan Tibetan Autonomous Prefecture as the place of case study and tourists as research objects. From the perspectives of geographical distribution of source tourist markets, Tourist activity behavioral and spatial patterns of Tourists, this study looks into the geographical structure of the source tourists and spatial patterns by geography. The analysis of 341 questionnaires on tourists shows that:(1) The tourism cycle of Gannan is in the development phase, competing with adjacent Aba, and greatly impacted by the substitution effect and shadow effect of Aba.(2) The spatial distribution of tourist sources is concentrated, indicating that Gannan is a regional tourism destination. The temporal distance of tourists is mainly concentrated within the 6-hour traffi c circle.(3) Gannan Tibetan Autonomous Prefecture has already become the composite tourist destination dominated by leisure vacation. The minority folkcustom and special landscape are the most attractive tourism resources. Due to the impact of man-land harmonious lifestyle in the tourist areas, the environmental attitude of tourists is improved, and the transportation and shopping are the most vulnerable links in tourism service in Gannan Tibetan Autonomous Prefecture.(4) The spatial behavior of tourists in Gannan is mainly of single-destination style(52%), Transit leg and circle tour style(7%) as well as circle tour style(41%). The spatial distribution of tourist fl ow in Gannan shows a signifi cant feature "more in the north, less in the south and dependent on National Road". Tourism resources, transport facilities, regional competition and lack of route connecting different ecological units are important causes of the spatial distribution of self-help tourists.
基金National Natural Science Foundation of China(Grant No.52178019).
文摘GPS positioning data are increasingly utilized in environmental behavior studies to explore the spatial-temporal behavioral patterns of individuals.However,individuals’stay behavioral pattern and its influencing factors,which are particularly significant for the design and management of scenic architectural complexes,have not been thoroughly examined.Using GPS trajectory data collected from the Palace Museum in Beijing(China),this paper investigated the visitors’stay behavior patterns associated with temporal,spatial,and environmental influencing factors.Types of stay behavior and characteristics of stay in main stay areas were automatically recognized using Python algorithms for further and quantitative analysis.Results showed that visitors’stay time exhibited a consistent pattern regarding psychological time allocation,a relatively unsignificant pattern regarding lunch hour,and no clear pattern regarding fatigue feature.Grouped regression analysis showed positive linear relationships with similar slopes between the average stay length and the number of stay occurrences in each type of stay area.Partial correlation analysis revealed the underlying connection between the impact of seats and greenery on stay behavior.Individually,each of the two environmental elements showed limited effect on stay frequency and stay length,while incorporating greenery into seating areas would notably increase both stay frequency and stay length.
文摘In accounts of the development and progression of psychophysical disorders such as Hereditary Spastic Paraplegia (HSP) and Facioscapulohumeral Muscular Dystrophy (FSHD), the role of beliefs, perceptions, and behavioral patterns has often been overlooked in favor of a genetically determinist paradigm. This paper explores the impact of NeuroPhysics Treatment (NPT) on patients with HSP and FSHD. Through a series of clinical case reports, I demonstrate how intensive four-day NPT sessions can lead to rapid restoration of lost functions, challenging the conventional view of these disorders. I hypothesize that, by modulating the patient’s perceptual and behavioral frameworks, NPT facilitates the emergence of healthier patterns, suggesting that environmental and psychological factors significantly influence the manifestation and management of these conditions. These findings indicate that the role of genetic inheritance may be overstated and that beliefs and perceptions could play a crucial role in the evolution of psychophysical disorders. The implications of this research extend beyond the traditional treatment paradigms, advocating for a more holistic approach that integrates the psychophysical dimensions of health and challenges the deterministic perspective of genetic inheritance.
文摘Trajectory clustering and behavior pattern extraction are the foundations of research into activity perception of objects in motion. In this paper, a new framework is proposed to extract behavior patterns through trajectory analysis. Firstly, we introduce directional trimmed mean distance （DTMD）, a novel method used to measure similarity between trajectories. DTMD has the attributes of anti-noise, self-adaptation and the capability to determine the direction for each trajectory. Secondly, we use a hierarchical clustering algorithm to cluster trajectories. We design a length-weighted linkage rule to enhance the accuracy of trajectory clustering and reduce problems associated with incomplete trajectories. Thirdly, the motion model parameters are estimated for each trajectory＇s classification, and behavior patterns for trajectories are extracted. Finally, the difference between normal and abnormal behaviors can be distinguished.
基金co-supported by the National Key R&D Program of China(No.2021YFA0715202)the National Natural Science Foundation of China(Nos.62022092,61790550,62171453)the Outstanding Youth Innovation Team Program of University in Shandong Province,China(No.2021KJ005).
文摘Trajectory data mining is widely used in military and civil applications,such as early warning and surveillance system,intelligent traffic system and so on.Through trajectory similarity measurement and clustering,target behavior patterns can be found from massive spatiotemporal trajectory data.In order to mine frequent behaviors of targets from complex historical trajectory data,a behavior pattern mining algorithm based on spatiotemporal trajectory multidimensional information fusion is proposed in this paper.Firstly,spatial–temporal Hausdorff distance is pro-posed to measure multidimensional information differences of spatiotemporal trajectories,which can distinguish the behaviors with similar location but different course and velocity.On this basis,by combining the idea of k-nearest neighbor and density peak clustering,a new trajectory clustering algorithm is proposed to mine behavior patterns from trajectory data with uneven density distribu-tion.Finally,we implement the proposed algorithm in simulated and radar measured trajectory data respectively.The experimental results show that the proposed algorithm can mine target behavior patterns from different complex application scenarios more quickly and accurately com-pared to the existing methods,which has a good application prospect in intelligent monitoring tasks.
文摘This study examines the database search behaviors of individuals, focusing on gender differences and the impact of planning habits on information retrieval. Data were collected from a survey of 198 respondents, categorized by their discipline, schooling background, internet usage, and information retrieval preferences. Key findings indicate that females are more likely to plan their searches in advance and prefer structured methods of information retrieval, such as using library portals and leading university websites. Males, however, tend to use web search engines and self-archiving methods more frequently. This analysis provides valuable insights for educational institutions and libraries to optimize their resources and services based on user behavior patterns.
文摘The present study has evaluated the effect of architectural forms on the walking activity of citizens as a behavioral model in urban physical spaces.The research hypothesis claims that by designing purposeful and appropriate architectural forms,the behavior and actions of users in urban physical spaces can be to some extent,it designed or controlled,and that the pattern and domains of human behavior in urban streets are the result of the components of environmental quality that are included in the design of that street.The present theoretical proposition has been tested in two sequences from Valiasr Street in Tehran.At the theoretical level,the research method is descriptive-analytical and at the experimental level,it is a survey that has been done using the behavioral research method.The results show that the floor form and street form are the most influential architectural forms in urban physical spaces on the activity of users walking from space in the study sample.Also,some environmental factors have a direct effect on human reactions;The research findings show that people’s speed is directly related to the dimensions of sidewalk carpets and a person tries to take a step according to the senses he receives from the sidewalk flooring form and as a result his speed changes according to those forms.
文摘The prevalence of HIV in high risk population is influenced significantly the behavioral and sociodemographic characteristics. However, considering the complexity of behavior among female sex workers, the relationship between a particular behavioral pattern and the HIV status of this “at risk” population assumes significance. Data generated in a community-based cross-sectional study earlier carried out to assess the prevalence estimates, at district level, of HIV status in eight districts of State of Andhra Pradesh, India was used to carry out factor analysis to explore the role of demographic and behavioral pattern and their relationship with the HIV status among female sex workers. Data on 3083 female sex workers in the study revealed that there existed nine patterns among demographic and behavioral characteristics, which explained 62% of the total variation through factor analysis. Further, cluster analysis was performed to identify the groups of individuals having similar characteristics. Two of those clusters had sizeable numbers having similar characteristics. FSWs belonging to cluster 2 had significantly high risk factors compared with Cluster 1. The overall prevalence of HIV was 11.4% (10.6% in cluster 1 and 15.9% in cluster 2) among high risk population. There exists a strong relationship between behavioral patterns and HIV positive.
基金Research and Development Program of Xi’an Modern Chemistry Research Institute of Chnia(Grant No.204J201916234/6)Key Project of Liuzhou Science and Technology Bureau of China(Grant No.2020PAAA0601).
文摘Selecting the optimal speed for dynamic obstacle avoidance in complex man–machine environments is a challenging problem for mobile robots inspecting hazardous gases.Consideration of personal space is important,especially in a relatively narrow man–machine dynamic environments such as warehouses and laboratories.In this study,human and robot behaviors in man–machine environments are analyzed,and a man–machine social force model is established to study the robot obstacle avoidance speed.Four typical man–machine behavior patterns are investigated to design the robot behavior strategy.Based on the social force model and man–machine behavior patterns,the fuzzy-PID trajectory tracking control method and the autonomous obstacle avoidance behavior strategy of the mobile robot in inspecting hazardous gases in a relatively narrow man–machine dynamic environment are proposed to determine the optimal robot speed for obstacle avoidance.The simulation analysis results show that compared with the traditional PID control method,the proposed controller has a position error of less than 0.098 m,an angle error of less than 0.088 rad,a smaller steady-state error,and a shorter convergence time.The crossing and encountering pattern experiment results show that the proposed behavior strategy ensures that the robot maintains a safe distance from humans while performing trajectory tracking.This research proposes a combination autonomous behavior strategy for mobile robots inspecting hazardous gases,ensuring that the robot maintains the optimal speed to achieve dynamic obstacle avoidance,reducing human anxiety and increasing comfort in a relatively narrow man–machine environment.
基金supported by National Natural Science Foundation of China(Grant 32300938).
文摘Process data recorded by computer-based assessments reflect how respondents solve problems and thus contain rich information about respondents as well as tasks.Considering that different respondents may exhibit different behavioral characteristics during problem-solving process,in this study,we propose a mixture one-parameter state response(Mix1P-SR)measurement model.This model assumes that respondents belong to discrete latent classes with different propensities towards responses to task states during the problem-solving process,and the varying response propensities are captured by different state parameters across classes.A Markov Chain Monte Carlo algorithm for the estimation of model parameters and classification of respondents is described.The simulation study shows that the Mix1P-SR model could recover parameters well on the premise that the average sequence length was not too short.Moreover,larger sample size,longer sequences,more uniform mixing proportions,and lower interclass similarity facilitated model convergence,model selection,and parameter estimation accuracy,with sequence length being particularly important.Based on the empirical data from PISA 2012,the Mix1P-SR model identified two latent classes of respondents.They had different patterns of state easiness parameters and exhibited different state response patterns,which affected their problem solving results.Implications for model application and future research directions are discussed.
