Statistical analyses were performed using procedures in IBM SPSS Statistic 22.0 and IBM SPSS Amos 22.0. First, descriptive statistics (means, standard deviations, correlations, and checks for normality) were computed for variables using IBM SPSS Statistic 22.0. Second, confirmatory factor analyses (CFA) were conducted for the measurement model. Then, structural equation modeling (SEM) analyses examining direct and indirect effects in the proposed conceptual model were performed by using procedures in IBM SPSS Amos 22.0 with the maximum likelihood (ML) estimation. The measurement property of the structural model was first examined, followed by an assessment of the proposed structural relationships (Anderson and Gerbing, 1988 (link)). Goodness of fit indices were assessed by using the comparative fit index (CFI), normed chi-square (χ2/df), standardized root mean square residual (SRMR), and root mean square error of approximation (RMSEA). The reliability of the measures was assessed by Cronbach’s alpha, Average Variance Extracted (AVE), and composite reliability. The convergent validity and discriminant validity were examined by factor loadings and the inter-factor correlations (Fornell and Larcker, 1981 (link); Kline, 2005 ; Hair et al., 2010 ).
Spss amos 22
Manufactured by IBM
Sourced in United States
SPSS AMOS 22.0 is a software package used for structural equation modeling (SEM), path analysis, and confirmatory factor analysis. It provides a graphical user interface for building and testing complex models. The software is designed to help researchers and analysts understand relationships between variables and test hypotheses.
Automatically generated - may contain errors
Lab products found in correlation
Spss statistics 22, by IBM (4 mentions)
Spss 22 for windows, by IBM (2 mentions)
Spss 21, by IBM (2 mentions)
Spss version 22, by IBM (2 mentions)
Spss statistic 22, by IBM (2 mentions)
Spss release 21, by IBM (1 mentions)
Spss process, by IBM (1 mentions)
Spss statistics 23, by IBM (1 mentions)
Spss 26, by IBM (1 mentions)
Spss statistics 26, by IBM (1 mentions)
Spss statistics 17, by IBM (1 mentions)
Stata 13, by StataCorp (1 mentions)
Statistical package for the social sciences version 25, by IBM (1 mentions)
Spss 24, by IBM (1 mentions)
Mestrenova, by Mestrelab Research (1 mentions)
Spss 22, by IBM (1 mentions)
Spss statistics 24, by IBM (1 mentions)
Spss 20.0 for windows, by IBM (1 mentions)
41 protocols using spss amos 22
1
Structural Equation Modeling of Research Model
2
Multivariate Statistical Analysis Protocol
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
SPSS 22.0 and SPSS Amos 22.0 were used as the major statistical analysis tool for experimental data. The statistical analysis methods included structural equation modeling analysis (SEM), reliability analysis, validity analysis (confirmatory factor analysis), correlation analysis, and independent samples t test.
3
Assessing Psychometric Properties of a Scale
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The methods of descriptive and analytical statistics were applied. The internal consistency of the scale was assessed using Cronbach’s alpha. The test–retest consistency was assessed using the intraclass correlations coefficients (ICC). For the factor analysis, the total sample was randomly divided into two samples, each including approximately 50% of the participants.
The exploratory factor analysis (EFA) was done to explore the factor structure and was done on one-half of the sample. The extraction of factors was done using Promax rotation, as the hypothesis was that the factors were correlated. Values for the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy and Bartlett’s test of sphericity (preferably significant) were used to assess the suitability of the data for factorization. The criterion for loading and cross-loading was set at 0.4. The confirmatory factor analysis (CFA) was done on the second half of the sample (selected randomly). The goodness of fit indices used were the goodness of fit index (GFI), adjusted goodness of fit index (AGFI), the comparative fit index (CFI), and the root mean error of approximation (RMSEA). The CFA was done using SPSS Amos 22.0 (Windows, Armonk, NY, USA). The missing values were replaced using the series mean. The analyses were done using the Statistical Package for Social Sciences (SPSS) for Windows 22.0 (Armonk, NY, USA).
The exploratory factor analysis (EFA) was done to explore the factor structure and was done on one-half of the sample. The extraction of factors was done using Promax rotation, as the hypothesis was that the factors were correlated. Values for the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy and Bartlett’s test of sphericity (preferably significant) were used to assess the suitability of the data for factorization. The criterion for loading and cross-loading was set at 0.4. The confirmatory factor analysis (CFA) was done on the second half of the sample (selected randomly). The goodness of fit indices used were the goodness of fit index (GFI), adjusted goodness of fit index (AGFI), the comparative fit index (CFI), and the root mean error of approximation (RMSEA). The CFA was done using SPSS Amos 22.0 (Windows, Armonk, NY, USA). The missing values were replaced using the series mean. The analyses were done using the Statistical Package for Social Sciences (SPSS) for Windows 22.0 (Armonk, NY, USA).
4
Assessing Scale Reliability and Validity
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The data were analyzed using SPSS for Windows 22.0 for frequency distribution, item analysis, EFA, and internal consistency. CFA was carried out using SPSS Amos 22.0. Item analysis was used to examine the correlations between each item and the overall scale, with the recommended corrected item-total correlations ranging from 0.3 to 0.7 (Ferketich, 1991) . After the item analysis, the reliability and validity of the scale were tested with the revised items. Statistical significance was considered as p b 0.05.
5
Money Attitudes of the Nenets People
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Attitude to money was studied using A. Furnham's questionnaire "Money Beliefs and Behavior Scale" in the adaptation of O.S. Deineka (1999) . Furnham was the first who proposed to explore money attitudes through the multifactorial questionnaire instead of using standardized techniques (Furnham, 1984) because of the flexibility that characterizes attitudes. The questionnaire consists of 45 items.
The study involved 75 people -representatives of the Nenets nationality aged 17 to 73 years (average age 28.6) living in the Yamal-Nenets Autonomous District (Aksarka village, Yar-Sale village) and the Nenets Autonomous District (Naryan-Mar city, Nes village, Krasnoye village). The form of the questionnaire was presented to the respondents in hard copy during the Reindeer Breeder Day celebration. The respondents 'behavior, the clarification questions they asked, and the time of completion were fixed (the average time for filling the questionnaire was 20 minutes).
To substantiate the structure of money attitudes of the Nenets, an exploratory factor analysis was performed based on the method of principal components with Varimax rotation. When processing the data, a statistical package SPSS 24.0 was used, including the structural equation software IBM SPSS AMOS 22. (IBM Corporation, Armonk, NY, USA).
The study involved 75 people -representatives of the Nenets nationality aged 17 to 73 years (average age 28.6) living in the Yamal-Nenets Autonomous District (Aksarka village, Yar-Sale village) and the Nenets Autonomous District (Naryan-Mar city, Nes village, Krasnoye village). The form of the questionnaire was presented to the respondents in hard copy during the Reindeer Breeder Day celebration. The respondents 'behavior, the clarification questions they asked, and the time of completion were fixed (the average time for filling the questionnaire was 20 minutes).
To substantiate the structure of money attitudes of the Nenets, an exploratory factor analysis was performed based on the method of principal components with Varimax rotation. When processing the data, a statistical package SPSS 24.0 was used, including the structural equation software IBM SPSS AMOS 22. (IBM Corporation, Armonk, NY, USA).
6
Psychometric Validation of NBQ-I
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The analysis was performed with the Italian version of the NBQ (NBQ-I) (17) . SPSS release 21.0 was used to perform the descriptive analyses and exploratory factor analysis. Confirmatory factor analysis was performed using IBM-SPSS Amos-22. RUMM2030 ( 21) was used for Rasch analysis.
7
Impact of Recruitment Letter Attributes
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The design was a 2 × 2 × 2 factorial plan with a response latency of the notification letter (two weeks vs. two months), a politeness formula of the letter (formal vs. informal), and customisation of the letter (anonymous vs. personalised with the candidate’s name) as between-subjects variables. With the aim of testing hypotheses, correlation and regression analyses with SPSS 21.0 (IBM, Armonk, NY, USA), were conducted. Moreover, we tested the proposed model through SEM using SPSS AMOS 22 (IBM, Armonk, NY, USA). Lastly, the possible role of manipulation of the feedback process on perceptions was explored through ANOVA and moderated mediation analysis with SPSS PROCESS (IBM, Armonk, NY, USA) (Dawson, 2013).
8
Validating Translated Questionnaires for Research
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Data analysis will be performed using IBM SPSS Statistics 23 and IBM SPSS AMOS 22. Descriptive statistics will be used for displaying the frequencies, percentages, means or medians, and standard deviation and a 95% confidence interval will be reported where relevant. An explorative factor analysis (EFA) and confirmatory factor analysis (CFA) will be conducted to test the translated questionnaires for psychometric properties. Possible associations between variables will be evaluated by hypothesis tests and/or generalized linear models and generalized estimating equations to compare the results over time, and an inductive qualitative content analysis [46 (link)] will also be conducted to analyse qualitative data.
9
Reliability and Validity Assessment of Psychological Scales
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The data were analyzed with the Statistical Package for the Social Sciences (SPSS- IBM®) Version 22.0. For the confirmatory factor analysis (CFA), the SPSS AMOS 22 (IBM®) was used. While arithmetic means and minimum and maximum values were used to determine the numerical data, numbers and percentages were used to determine the categorical data. For the reliability analysis, the internal consistency analysis methods were used. These methods were as follows: (1) item-total correlations (to determine the item reliability), (2) Cronbach's alpha (to determine the homogeneity), and (3) test–retest and Pearson product-moment correlation coefficient (to determine the stability of the scale over time). The value ≥0.30 was used as the criterion for the item-total correlation.[26 ] While the content validity index was used for the content validity of the scale, the exploratory factor analysis (EFA) and CFA were used for the factor construct validity. To determine the suitability of the data for the factor analysis, Kaiser–Meyer–Olkin (KMO) value and Bartlett's test were used.[20 21 (link)22 (link)] For the calculation of the factor analysis, the Varimax rotation method was also used.
10
Construct Validation of Research Scale
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All analyses were carried out using the IBM SPSS 26.0 and IBM SPSS Amos 22 software. After the descriptive analysis was done, exploratory (EFA) and confirmatory (CFA) factor analyses were conducted to test the construct validity of the scale. Maximum Likelihood analysis as a factor extraction method with Varimax rotation method was used in the EFA. Items with factor loadings ≥ 0.40 were accepted (Tsai et al. 2015 (link)). In the CFA, p values less than 0.05 were considered statistically significant. Internal consistency of the scale and subscales was assessed by Cronbach’s alpha, with 0.70 set as the criterion for internal consistency reliability (Hair et al. 2010 ).
About PubCompare
Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.
We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.
However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.
Ready to get started?
Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required
Revolutionizing how scientists
search and build protocols!