scholarly journals For whom did telework not work during the Pandemic? understanding the factors impacting telework satisfaction in the US using a multiple indicator multiple cause (MIMIC) model

2022 ◽  
Vol 155 ◽  
pp. 387-402
Author(s):  
Divyakant Tahlyan ◽  
Maher Said ◽  
Hani Mahmassani ◽  
Amanda Stathopoulos ◽  
Joan Walker ◽  
...  
Keyword(s):  
Mimic Model ◽  
The Us ◽  
Multiple Indicator

scholarly journals Comparing multiple statistical software for multiple-indicator, multiple-cause modeling: an application of gender disparity in adult cognitive functioning using MIDUS II dataset

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Chi Chang ◽  
Joseph Gardiner ◽  
Richard Houang ◽  
Yan-Liang Yu
Keyword(s):  
Cognitive Functioning ◽  
Latent Variable ◽  
The United States ◽  
Equation Modeling ◽  
Statistical Software ◽  
Mimic Model ◽  
Empirical Application ◽  
Data Manipulation ◽  
Software Packages ◽  
Multiple Indicator

Abstract Background The multiple-indicator, multiple-cause model (MIMIC) incorporates covariates of interest in the factor analysis. It is a special case of structural equation modeling (SEM), which is modeled under latent variable framework. The MIMIC model provides rigorous results and becomes broadly available in multiple statistical software. The current study introduces the MIMIC model and how it can be implemented using statistical software packages SAS CALIS procedure, R lavaan package, and Mplus version 8.0. Methods In this paper, we first discussed the formulation of the MIMIC model with regard to model specification and identification. We then demonstrated the empirical application of the MIMIC model with the Midlife in the United States II (MIDUS II) Study (N = 4109) using SAS CALIS procedure, R lavaan package and Mplus version 8.0 to examine gender disparities in cognitive functioning. The input, output, and diagram syntaxes of the three statistical software packages were also presented. Results In terms of data structure, all three statistical programs can be conducted using both raw data and empirical covariance matrix. SAS and R are comprehensive statistical analytic packages and encompass numerous data manipulation capacities. Mplus is designed primarily for latent variable modeling and has far more modeling flexibility compared to SAS and R, but limited in data manipulation. Differences in model results from the three statistical programs are trivial. Overall, the results show that while men show better performance in executive function than women, women demonstrate better episodic memory than men. Conclusions Our study demonstrates the utility of the MIMIC model in its empirical application, fitted with three popular statistical software packages. Results from our models align with empirical findings from previous research. We provide coding procedures and examples with detailed explanations in the hopes of providing a concise tutorial for researchers and methodologists interested in incorporating latent constructs with multiple indicators and multiple covariates in their research projects. Future researchers are encouraged to adopt this flexible and rigorous modeling approach.

Sport Stadium Atmosphere: Formative and Reflective Indicators for Operationalizing the Construct

2010 ◽  
Vol 24 (2) ◽  
pp. 211-237 ◽  
Author(s):  
Sebastian Uhrich ◽  
Martin Benkenstein
Keyword(s):  
Delphi Study ◽  
Team Sports ◽  
Affective Responses ◽  
Social Aspects ◽  
Future Research ◽  
Theoretical Construct ◽  
Mimic Model ◽  
Multiple Indicator ◽  
Sport Events ◽  
Special Atmosphere

This article reports the findings of an investigation into the atmosphere in stadiums during live team sports. Experiencing this special atmosphere represents an essential part of the total service provided by the organizers of sport events. However, existing research into the concept of atmosphere focuses on the retail environment. Our first step was therefore to define sport stadium atmosphere as a theoretical construct, drawing on theories from environmental psychology. We then developed a mimic (multiple indicator-multiple cause) model to measure the construct. To specify the mimic model, we generated and selected formative measures by means of a delphi study (N= 20), qualitative expert interviews (N= 44), and an indicator sort task (N= 34). The results indicate that various physical and social aspects of the stadium environment are causal indicators of sport stadium atmosphere. Following this, we conducted phenomenological interviews with spectators at sport events (N= 5) to identify typical affective responses to stadium environment (representing the reflective indicators of the mimic model). These interviews revealed that fans’ experience of stadium environment is characterized by high levels of arousal and pleasure. In addition to our findings, the mimic model developed in this study represents a useful tool for future research into sport stadium atmosphere.

scholarly journals Dissatisfied, feeling unequal and inclined to emigrate: Perceptions from Macedonia in a MIMIC model

2015 ◽  
Vol 12 (3) ◽  
pp. 300-314 ◽  
Author(s):  
Marjan Petreski ◽  
Blagica Petreski
Keyword(s):  
Financial Constraints ◽  
Economic Environment ◽  
Continuous Variables ◽  
Ethnic Inequality ◽  
Emigration Rate ◽  
Mimic Model ◽  
Ethnic Inequalities ◽  
Multiple Indicator

Macedonia has a large diaspora, a high emigration rate and receives larger volume of remittances. This paper aims to describe the current inclination to emigrate from Macedonia, in the light of the dissatisfaction with the domestic political and economic environment and the potential feeling of gender and ethnic inequalities. Particular reference is made to the role of remittances. We use the Remittances Survey 2008 and treat dissatisfaction, feeling of inequality and inclination to emigrate as latent continuous variables in a MIMIC (Multiple-Indicator Multiple-Cause) model, observed only imperfectly in terms of respondents’ perceptions and opinions. Results suggest that dissatisfaction with the societal conditions in Macedonia grows among those who are at their 20s and early 30s, which is more prevalent among ethnic Albanians. Compared to others, Albanians also demonstrate stronger feeling of gender and ethnic inequality. Dissatisfaction, but not the feeling of inequality, then feeds inclination to emigrate. Further to this, however, males and less educated persons are more inclined to emigrate, irrespective of their level of dissatisfaction. We find remittances to play a strong role for the inclination to emigrate: the inclination is larger in households receiving remittances and increases with the amount received, as it is likely that remittances alleviate financial constraints for other persons of the household to emigrate.

scholarly journals Comparing Multiple Statistical Software for Multiple-Indicator, Multiple-Cause Modeling: An Application of Gender Disparity in Adult Cognitive Functioning Using MIDUS II Dataset

2020 ◽  
Author(s):  
Chi Chang ◽  
Joseph Gardiner ◽  
Richard T Houang ◽  
Yan-Liang Yu
Keyword(s):  
Cognitive Functioning ◽  
Latent Variable ◽  
The United States ◽  
Equation Modeling ◽  
Statistical Software ◽  
Mimic Model ◽  
Empirical Application ◽  
Data Manipulation ◽  
Software Packages ◽  
Multiple Indicator

Abstract Background The Multiple-indicator, multiple-cause model (MIMIC) incorporates covariates of interest in the factor analysis is a special case of structural equation modeling (SEM), which is modeled under latent variable framework. The MIMIC model provides rigorous results and becomes broadly available in multiple statistical software. The current study introduces the MIMIC model and how it can be implemented using statistical software packages SAS CALIS procedure, R lavaan package, and Mplus version 8.0. Methods In this paper, we first discussed the formulation of the MIMIC model with regard to model specification and identification. We then demonstrated the empirical application of the MIMIC model with the Midlife in the United States II (MIDUS II) Study (N=4,109) using SAS CALIS procedure, R lavaan package and Mplus version 8.0 to examine gender disparities in cognitive functioning. The input, output, and diagram syntaxes of the three statistical software packages were also presented.Results In terms of data structure, all three statistical programs can be conducted using both raw data and empirical covariance matrix. SAS and R are comprehensive statistical analytic packages and encompass numerous data manipulation capacities. Mplus is designed primarily for latent variable modeling and has far more modeling flexibility compared to SAS and R, but limited in data manipulation. Differences in model results from the three statistical programs are trivial. Overall, the results show that while men show better performance in executive function than women, women demonstrate better episodic memory than men.Conclusions Our study demonstrates the utility of the MIMIC model in its empirical application, fitted with three popular statistical software packages. Results from our models align with empirical findings from previous research. We provide coding procedures and examples with detailed explanations in the hopes of providing a concise tutorial for researchers and methodologists interested in incorporating latent constructs with multiple indicators and multiple covariates in their research projects. Future researchers are encouraged to adopt this flexible and rigorous modeling approach.

scholarly journals Fulfillment Sentiment and Inclusive Identity: A Multiple-Indicator Multiple-Cause (MIMIC) Model

2004 ◽  
Vol 52 (3) ◽  
pp. 320-330 ◽  
Author(s):  
HISASHI OHNO ◽  
MADOKA MOGAKI ◽  
AKIKO MIYOSHI ◽  
KAE UCHIJIMA
Keyword(s):  
Mimic Model ◽  
Multiple Indicator

scholarly journals Pengaplikasian Multiple Indicator Multiple Causes (MIMIC) Model dalam Mendeteksi Differential Item Functioning (DIF) pada Alat Ukur Social Quality of Life

2019 ◽  
Vol 8 (1) ◽  
pp. 25-36
Author(s):  
Hasbi Wahyudi
Keyword(s):  
Quality Of Life ◽  
Differential Item Functioning ◽  
Mimic Model ◽  
Social Quality ◽  
Item Functioning ◽  
Patient Reported ◽  
Social Quality Of Life ◽  
Multiple Indicator ◽  
Multiple Causes

AbstractThis study aims to detect DIF (differential item functioning) on a quality of life measurement tool that measures one aspect, namely social quality of life. Social quality of life contains 24 items developed from the Patient Reported Outcomes Measurement Information System (PROMIS) by a National Institutes of Health (NIH). This measuring tool measures the quality of life in the social function domain of adolescent patients suffering from diseases or chronic medical conditions. Detection of DIF in this study uses a special case approach from CFA, namely CFA with covariate or multiple indicator multiple causes (MIMIC) models. This study involved 322 participants, 117 (36%) male participants and 205 (64%) female participants, with an age range between 13-23 years in Riau Province. Based on the results of the first order CFA on a set of social quality of life items there are 22 valid items. Then the MIMIC model analysis results found that the model is fit with data where the value of RMSEA = 0.048, so it is known two items that contain DIF, namely item 5 (0.135, P = 0.002) "I have a close friend" and item 23 (0.308, P = 0.002 ) "I hope to have lots of friends".Keywords: Social quality of life, MIMIC model, differential item functioningAbstrakPenelitian ini bertujuan untuk mendeteksi DIF (differential item functioning) pada alat ukur quality of life yang mengukur salah satu aspek yaitu social quality of life. Social quality of life berisi 24 item yang dikembangkan dari Patient Reported Outcomes Measurement Information System (PROMIS) oleh sebuah badan National Institutes of Health (NIH). Alaalat ukur ini mengukur kualitas hidup pada domain fungsi sosial pasien remaja yang menderita penyakit atau kondisi medis kronis. Pendeteksian DIF pada penelitian ini menggunakan pendekatan kasus khusus dari CFA, yakni CFA with covariate atau multiple indicator multiple causes (MIMIC) model. Penelitian ini melibatkan 322 partisipan, yakni sebanyak 117 (36%) partisipan laki-laki dan 205 (64%) partisipan perempuan, dengan rentang usia antara 13-23 tahun di Propinsi Riau. Berdasarkan hasil first order CFA pada sekumpulan item-item social quality of life terdapat 22 item yang valid. Kemudian hasil analisis model MIMIC ditemukan bahwa model fit dengan data dimana nilai RMSEA = 0.048, sehingga diketahui dua item yang mengandung DIF, yaitu item 5 (0.135, P = 0.002) “saya memiliki teman dekat” dan item 23 (0.308, P = 0.002) “saya berharap mempunyai banyak teman”.Kata kunci: Social quality of life, MIMIC model, differential item functioning

scholarly journals Comparing Multiple Statistical Software for Multiple-Indicator, Multiple-Cause Modeling: An Application of Gender Disparity in Adult Cognitive Functioning Using MIDUS II Dataset

2020 ◽  
Author(s):  
Chi Chang ◽  
Joseph Gardiner ◽  
Richard T Houang ◽  
Yan-Liang Yu
Keyword(s):  
Structural Equation Modeling ◽  
Cognitive Functioning ◽  
Structural Equation ◽  
The United States ◽  
Equation Modeling ◽  
Statistical Software ◽  
Mimic Model ◽  
Empirical Application ◽  
Data Manipulation ◽  
Multiple Indicator

Abstract Background: The Multiple-indicator, multiple-cause model (MIMIC) incorporates covariates of interest in the factor analysis using structural equation modeling framework. The model provides rigorous results and becomes broadly available in multiple statistical software. The current study introduces the MIMIC model and how it can be implemented using statistical software SAS CALIS procedure, R lavaan package, and M plus version 8.0. Methods: In this paper, we first discussed the formulation of the MIMIC model with regard to model specification and identification. We then demonstrated the empirical application of the MIMIC model with the Midlife in the United States II (MIDUS II) Study (N=4,109) using SAS CALIS procedure, R lavaan package and M plus version 8.0 to examine gender disparities in cognitive functioning. The input, output, and diagram syntaxes of the three statistical software programs were also presented. Results In terms of data structure, all three statistical programs can be conducted using both raw data and empirical covariance matrix. While SAS and R are comprehensive statistical analytic packages and encompass numerous data manipulation capacities, M plus is designed primarily for structural equation modeling and therefore is limited in data manipulation. Differences in model results from the three statistical programs are trivial. Overall, the results show that while men show better performance in executive function than women, women demonstrate better episodic memory than men. Conclusions: Our study demonstrates the utility of the MIMIC model in its empirical application, fitted with three popular statistical software packages. Results from our models align with empirical findings from previous research. We provide coding procedures and examples with detailed explanations in the hopes of providing a concise tutorial for researchers and methodologists interested in incorporating latent constructs with multiple indicators and multiple covariates in their research projects. Future researchers are encouraged to adopt this flexible and rigorous modeling approach.

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