Notes

CMF as well as MET treatment cause mental incapacity by means of upregulation involving IL-1α in rat mind.
Different studies have highlighted the importance of subjective outcomes in negotiations. The Subjective Value Inventory (SVI) is the only existing instrument for measuring this aspect. The aim of this research was to analyze the psychometric properties and gender factorial invariance of the SVI in a Spanish sample.

A double back-translation of the original tool was carried out and it was then applied to a diverse sample of 345 university students and professionals of both genders. Analysis of factorial validity, reliability, and factorial invariance of the model across gender were carried out.

A model of sixteen items grouped into four factors, equivalent to the original, was confirmed. All the factors of the model, except the Self, demonstrated adequate psychometric indices. The configural invariance across gender is acceptable.

The Spanish version of the SVI matches the original scale. Acetalax mouse However, this study proposes using the scale without the Self factor. Lastly, the scale shows configural invariance across gender.
The Spanish version of the SVI matches the original scale. However, this study proposes using the scale without the Self factor. Lastly, the scale shows configural invariance across gender.
Sexual fantasies are described as thoughts or mental images with sexual content. The Hurlbert Index of Sexual Fantasy (HISF) evaluates the positive attitude towards sexual fantasies. The objective of this study was to provide validity evidence of the Spanish version of the HISF and to present its standard scores.

The sample was composed of 3,458 adults from the general Spanish population (1,641 men; 1,817 women), distributed across age groups (18-34, 35-49, and over 50 years old).

The unifactorial structure of the Spanish version of the HISF showed strict measurement invariance across sex, age range, and education level. Positive attitudes towards sexual fantasies significantly correlated with erotophilia, sexual assertiveness, sexual desire, and sexual functioning. Also, the scale was useful for differentiating between individuals with sexual functioning difficulties and individuals with no difficulties. Finally, the standard scores were obtained based on sex and age range.

The Spanish version of the HISF is a reliable, valid, and invariant scale for assessing a positive attitude towards sexual fantasies in people with different sociodemographic characteristics.
The Spanish version of the HISF is a reliable, valid, and invariant scale for assessing a positive attitude towards sexual fantasies in people with different sociodemographic characteristics.
The Personal Outcomes Scale (POS) is used to assess quality of life (QoL) in people with intellectual disability (ID) but the results are influenced by the severity of the disability. To address this issue, we present the standardization of the Spanish adaptation of the POS. One of the limitations of the Classical Test Theory is the differential effect in some items due to the effect of an external variable. For this reason, we propose the use of multiple linear regressions.

We used a sample of 529 people with ID, along with 522 professionals and 462 parents who were administered the POS in order to carry out an in-depth psychometric study. For the analysis, we used the correction strategy by multiple linear regressions to generate centiles corrected for the severity effect of ID.

Following this technique, the results show the centiles from the raw POS score corrected for the effect of the severity of ID.

This standardization technique is a feasible option to provide a QoL scale without biased results due to the severity of ID.
This standardization technique is a feasible option to provide a QoL scale without biased results due to the severity of ID.
Although average-based effect size (ES) and percentage of individual changes (PIC) are quite different, they are not independent larger ESs lead to higher PICs. However, this association has not been sufficiently explored.

We analyzed this association based on data simulated in the context of a pre-post design, with and without control groups. We simulated various distributions, sample sizes, degrees of test-retest reliability, effect sizes, and different variances in pre- and post-test.

The PIC is closely associated with the ES across a wide variety of empirically frequent scenarios. In the "single group pre-post designs", the linear regression model shows R2 values above 0.90. In the "control group pre-post designs", the linear regression model shows R2 values above 0.80. These results were found even when the post-test variability differed from that of the pre-test, replicating, extending and generalizing the findings in previous studies.

(1) In the absence of information about the PIC, the ES may be used to estimate this percentage. (2) The PIC is useful in interpreting the meaning of ES measures.
(1) In the absence of information about the PIC, the ES may be used to estimate this percentage. (2) The PIC is useful in interpreting the meaning of ES measures.
This study analyzes the effectiveness of different information criteria for the selection of covariance structures, extending it to different missing data mechanisms, the maintenance and adjustment of the mean structures, and matrices.

The Monte Carlo method was used with 1,000 simulations, SAS 9.4 statistical software and a partially repeated measures design (p=2; q=5). The following variables were manipulated a) the complexity of the model; b) sample size; c) matching of covariance matrices and sample size; d) dispersion matrices; e) the type of distribution of the variable; f) the non-response mechanism.

The results show that all information criteria worked well in Scenario 1 for normal and non-normal distributions with heterogeneity of variance. However, in Scenarios 2 and 3, all were accurate with the ARH matrix, whereas AIC, AICCR and HQICR worked better with TOEP and UN. When the distribution was not normal, AIC and AICCR were only accurate in Scenario 3, more heterogeneous and unstructured matrices, with complete cases, MAR and MCAR.

In order to correctly select the matrix it is advisible to analyze the heterogeneity, sample size and distribution of the data.
In order to correctly select the matrix it is advisible to analyze the heterogeneity, sample size and distribution of the data.
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