Importance of allotigenic accessory elements in factor loading matrix as statistical expression of geochemical composition variation in soils of different age

Geologija ◽  
2008 ◽  
Vol 50 (2) ◽  
pp. 67-74 ◽  
Author(s):  
Olga Vareikienė ◽  
Rimantė Zinkutė ◽  
Alfredas Radzevičius
Keyword(s):  
Factor Loading ◽  
Geochemical Composition ◽  
Composition Variation ◽  
Loading Matrix

Factor Loading Matrix

2005 ◽  
Author(s):  
Ralph B. D'agostino ◽  
Heidy K. Russell
Keyword(s):  
Factor Loading ◽  
Loading Matrix

Target Rotation and Normative Policy Analysis in Urban Ecology

1978 ◽  
Vol 10 (3) ◽  
pp. 275-285 ◽  
Author(s):  
E D Perle
Keyword(s):  
Census Data ◽  
Urban System ◽  
Performance Standards ◽  
Factor Loading ◽  
Policy Implications ◽  
System Description ◽  
Target Matrix ◽  
Target Rotation ◽  
Vector Basis ◽  
Loading Matrix

Factor analytic methodology in geography and planning has been limited to system description. The conventional approach of searching for an underlying vector basis is germane for exploratory type research, but it is not directly applicable for normative purposes. Target rotation provides an analytical matrix-comparison methodology particularly useful in extending the utility of urban system findings from descriptive ecological studies to normative ones. An empirical example of this approach is provided, based upon 1970 census data of the Detroit SMSA. An empirical factor-loading matrix is presented, a target matrix of desirable performance standards is hypothesized, and the observed loadings are rotated upon the target loadings. Observed system performance is then directly compared with desired performance, indicating the direction and magnitude of convergence/divergence. Finally, policy implications of these empirical findings are suggested.

scholarly journals A Lognormal Ipsative Model for Multidimensional Compositional Items

2021 ◽  
Vol 12 ◽  
Author(s):  
Chia-Wen Chen ◽  
Wen-Chung Wang ◽  
Magdalena Mo Ching Mok ◽  
Ronny Scherer
Keyword(s):  
Latent Trait ◽  
Full Rank ◽  
Factor Loading ◽  
Parameter Recovery ◽  
Factor Loadings ◽  
Irt Model ◽  
Response Data ◽  
Proposed Model ◽  
High Convergence Rate ◽  
Loading Matrix

Compositional items – a form of forced-choice items – require respondents to allocate a fixed total number of points to a set of statements. To describe the responses to these items, the Thurstonian item response theory (IRT) model was developed. Despite its prominence, the model requires that items composed of parts of statements result in a factor loading matrix with full rank. Without this requirement, the model cannot be identified, and the latent trait estimates would be seriously biased. Besides, the estimation of the Thurstonian IRT model often results in convergence problems. To address these issues, this study developed a new version of the Thurstonian IRT model for analyzing compositional items – the lognormal ipsative model (LIM) – that would be sufficient for tests using items with all statements positively phrased and with equal factor loadings. We developed an online value test following Schwartz’s values theory using compositional items and collected response data from a sample size of N = 512 participants with ages from 13 to 51 years. The results showed that our LIM had an acceptable fit to the data, and that the reliabilities exceeded 0.85. A simulation study resulted in good parameter recovery, high convergence rate, and the sufficient precision of estimation in the various conditions of covariance matrices between traits, test lengths and sample sizes. Overall, our results indicate that the proposed model can overcome the problems of the Thurstonian IRT model when all statements are positively phrased and factor loadings are similar.

scholarly journals On the Equivalency of Factor and Network Loadings

2020 ◽  
Author(s):  
Alexander P. Christensen ◽  
Hudson Golino
Keyword(s):  
Factor Model ◽  
Network Models ◽  
High Sensitivity ◽  
Factor Loading ◽  
Random Factor ◽  
Factor Loadings ◽  
Network Measure ◽  
Confirmatory Factor ◽  
Similar Information ◽  
Loading Matrix

Recent research has demonstrated that the network measure node strength or sum of a node’s connections is roughly equivalent to confirmatory factor analysis (CFA) loadings. A key finding of this research is that node strength represents a combination of different latent causes. In the present research, we sought to circumvent this issue by formulating a network equivalent of factor loadings, which we call network loadings. In two simulations, we evaluated whether these network loadings could effectively (1) separate the effects of multiple latent causes and (2) estimate the simulated factor loading matrix of factor models. Our findings suggest that the network loadings can effectively do both. In addition, we leveraged the second simulation to derive effect size guidelines for network loadings. In a third simulation, we evaluated the similarities and differences between factor and network loadings when the data were generated from random, factor, and network models. We found sufficient differences between the loadings, which allowed us to develop an algorithm to predict the data generating model called the Loadings Comparison Test (LCT). The LCT had high sensitivity and specificity when predicting the data generating model. In sum, our results suggest that network loadings can provide similar information to factor loadings when the data are generated from a factor model and therefore can be used in a similar way (e.g., item selection, measurement invariance, factor scores).

scholarly journals Causal Discovery with Multi-Domain LiNGAM for Latent Factors

2021 ◽  
Author(s):  
Yan Zeng ◽  
Shohei Shimizu ◽  
Ruichu Cai ◽  
Feng Xie ◽  
Michio Yamamoto ◽  
...  
Keyword(s):  
Causal Structure ◽  
Score Function ◽  
Factor Loading ◽  
Real World Data ◽  
Latent Factors ◽  
Two Phase ◽  
Loading Matrix ◽  
Non Gaussian ◽  
Causal Structures

Discovering causal structures among latent factors from observed data is a particularly challenging problem. Despite some efforts for this problem, existing methods focus on the single-domain data only. In this paper, we propose Multi-Domain Linear Non-Gaussian Acyclic Models for LAtent Factors (MD-LiNA), where the causal structure among latent factors of interest is shared for all domains, and we provide its identification results. The model enriches the causal representation for multi-domain data. We propose an integrated two-phase algorithm to estimate the model. In particular, we first locate the latent factors and estimate the factor loading matrix. Then to uncover the causal structure among shared latent factors of interest, we derive a score function based on the characterization of independence relations between external influences and the dependence relations between multi-domain latent factors and latent factors of interest. We show that the proposed method provides locally consistent estimators. Experimental results on both synthetic and real-world data demonstrate the efficacy and robustness of our approach.

SEM study of quartz grains from recent sediments: Western Iraq

1990 ◽  
Vol 48 (4) ◽  
pp. 860-861
Author(s):  
F. Al-Kufaishi
Keyword(s):  
Factor Loading ◽  
Fault System ◽  
Clay Material ◽  
Crustal Material ◽  
Factor Analyses ◽  
Five Factors ◽  
Sem Study ◽  
Recent Sediments ◽  
Quartz Grains ◽  
Positive Factor

Two localities (Al-Marij and Laik) were selected to investigate the type of Quartz Grains from crustal material formed by evaporation of waters discharged by springs in Hit area, western Iraq, Previous studies on the crustal material (1,2) showed that the water discharged by these springs are associated with Abu-Jir fault system which run parallel to the Euphrates river,Factor analyses of the crustal and soil materials (50 samples analysed for 16 variables)(2) showed five factors; the first factor includes SiO2, Al2O3 and TiO2 with positive factor loading, and CaO, L.O.I. with negative loading and hence lead to the conclusion that the distribution of these variables is a reflection of transported clay material.This study concentrates on the use of SEM to investigate the contribution of Quartz grains found in the crustal material on two selected sites.

Variasi Penambahan Sika Cim Dan Fiber Kawat Pada Beton Mutu Fc’ 30 Mpa

2018 ◽  
Vol 9 (2) ◽  
pp. 67-73
Author(s):  
M Zainul Arifin
Keyword(s):  
Tensile Strength ◽  
Compressive Strength ◽  
Curing Temperature ◽  
Test Results ◽  
Concrete Compressive Strength ◽  
Normal Concrete ◽  
Astm Method ◽  
Additive Type ◽  
Composition Variation ◽  
Compressive Strength Of Concrete

This research was conducted to determine the value of the highest compressive strength from the ratio of normal concrete to normal concrete plus additive types of Sika Cim with a composition variation of 0.25%, 0.50%, 0.75%, 1.00%, 1.25%, 1 , 50% and 1.75% of the weight of cement besides that in this study also aims to find the highest tensile strength from the ratio of normal concrete to normal concrete in the mixture of sika cim composition at the highest compressive strength above and after that added fiber wire with a size diameter of 1 mm in length 100 mm with a ratio of 1% of material weight. The concrete mix plan was calculated using the ASTM method, the matrial composition of the normal concrete mixture as follows, 314 kg / m3 cement, 789 kg / m3 sand, 1125 kg / m3 gravel and 189 liters / m3 of water at 10 cm slump, then normal concrete added variations of the composition of sika cim 0.25%, 0.50%, 0.75%, 1.00%, 1.25%, 1.5%, 1.75% by weight of cement and fiber, the tests carried out were compressive strength of concrete and tensile strength of concrete, normal maintenance is soaked in fresh water for 28 days at 30oC. From the test results it was found that the normal concrete compressive strength at the age of 28 days was fc1 30 Mpa, the variation in the addition of the sika cim additive type mineral was achieved in composition 0.75% of the cement weight of fc1 40.2 Mpa 30C. Besides that the tensile strength test results were 28 days old with the addition of 1% fiber wire mineral to the weight of the material at a curing temperature of 30oC of 7.5%.

Hydrogeological responses in tropical mountainous springs

2019 ◽  
Author(s):  
Ricardo Sánchez-Murillo
Keyword(s):  
Costa Rica ◽  
Isotope Composition ◽  
Central Valley ◽  
Distribution Functions ◽  
Geochemical Composition ◽  
Transit Times ◽  
Management Plans ◽  
Best Fit ◽  
Term Data

This study presents a hydrogeochemical analysis of spring responses (2013-2017) in the tropical mountainous region of the Central Valley of Costa Rica. The isotopic distribution of δ18O and δ2H in rainfall resulted in a highly significant meteoric water line: δ2H = 7.93×δ18O + 10.37 (r2=0.97). Rainfall isotope composition exhibited a strong dependent seasonality. The isotopic variation (δ18O) of two springs within the Barva aquifer was simulated using the FlowPC program to determine mean transit times (MTTs). Exponential-piston and dispersion distribution functions provided the best-fit to the observed isotopic composition at Flores and Sacramento springs, respectively. MTTs corresponded to 1.23±0.03 (Sacramento) and 1.42±0.04 (Flores) years. The greater MTT was represented by a homogeneous geochemical composition at Flores, whereas the smaller MTT at Sacramento is reflected in a more variable geochemical response. The results may be used to enhance modelling efforts in central Costa Rica, whereby scarcity of long-term data limits water resources management plans.

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