We assessed the dynamics of national internet searches and potential triggering news related to the application of ivermectin throughout Hungary during the COVID-19 pandemic, beginning in January 2020 and extending through March 2021. The relative search volume for the term “ivermectin” for Hungary were downloaded from Google Trends (accessed on 16 April 2021) [34 ] and plotted against national coronavirus case data available from WHO confirmed cases of COVID-19 [35 ]. The statistical correlation was calculated using Pearson correlation to explore the relationship between Google Trends data (weekly relative search popularity) and WHO COVID-19 data (weekly confirmed COVID cases throughout Hungary). Data was analyzed using SPSS Statistics 26 for Windows. Relevant Hungarian online news articles were identified using a Google News aggregator (accessed on 16 April 2021) [36 ], specifically using the term “ivermectin”. Next, news articles were manually categorized by the authors described as either “potentially triggering” or “averting”.
Spss statistics 26 for windows
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SPSS Statistics 26 for Windows is a statistical software package that provides a comprehensive set of tools for data analysis, data management, and reporting. It offers a wide range of statistical procedures, including descriptive statistics, regression analysis, and hypothesis testing. SPSS Statistics 26 is designed to be user-friendly and offers a graphical user interface for easy data manipulation and visualization.
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Lab products found in correlation
58 protocols using spss statistics 26 for windows
1
Ivermectin Trends During COVID-19 in Hungary
2
Cyp Enzymes and Hormone Fluctuations
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All statistical analysis were performed with SPSS Statistics 26 for Windows. Descriptive statistics were calculated for demographics, biochemical parameters, hormone levels and Cyps concentrations. Normal distribution of variables was evaluated with Kolmogorov–Smirnov and Shapiro–Wilk tests. Data of variables with normal distribution are shown as mean ± SEM, whilst results of non-parametric variables are presented as median and interquartile range. Statistical differences across the cycle of variables with normal distribution were determined with repeated measures ANOVA and estimated marginal means (adjusted by Bonferroni method) tests. Friedman test and Dunn-Bonferroni post hoc test were used for non-parametric variables. Bivariate correlations between Cyps and hormone concentrations were determined with Spearman rank correlation coefficient. Significance level of p < 0.05 was set for all analyses.
3
Rigorous Statistical Analysis of Experimental Data
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All statistical analyses were performed using SPSS Statistics 26, for Windows (SPSS Inc., Chicago, IL, USA). The results were expressed as means ± standard error of mean (SEM). The normality of continuous variables was assessed using the Shapiro-Wilk test. Unpaired two-tailed Student’s t-tests between two groups and one-way ANOVA followed by LSD multiple comparison post hoc test was used to test differences among multiple groups. Statistical significance was set at *P < 0.05, **P < 0.01, ***P < 0.001 and ****P < 0.0001. GraphPad Prism v.8.0 (GraphPad Software) was used for statistical analysis.
4
Associations of DSWPD with Mental Health
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IBM SPSS Statistics 26 for Windows (SPSS Inc., Chicago, Ill) was used for all analyses. Independent sample t-tests and c 2 -tests were used to examine differences in sociodemographic, lifestyle and sleep variables in students with and without DSWPD. Sum scores on the mental and somatic health scales were converted to standardized t-scores (mean ¼ 50 and 1 SD ¼ 10) to ease comparisons across instruments, and between-group effect sizes (pooled SD) were calculated using the Cohen d formula. These effect sizes are usually interpreted according to Cohen's guidelines (Cohen, 1988) , with ds about 0.20, 0.50, and 0.80 representing small, moderate and large effect sizes, respectively. Logistic regression analyses were used to assess the association between DSWPD and the dichotomous variables (mental disorders and suicidality), adjusting for sex and age. Multiple testing corrections (BenjaminieHochberg) were applied to the results of statistical tests where appropriate.
5
Shoulder Pain Muscle Activity Analysis
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SPSS Statistics 26 for Windows (SPSS Science, Chicago, III) was used for statistical analysis. To compare the muscle activity between the two groups (shoulder pain and healthy controls), and between intervention (verbal/tactile session versus no intervention), a 3-way ANOVA for repeated measures for each muscle was performed, with one within-subject factor: time (2 levels: pre-and post-exercise) and 2 between-subject factors: group (2 levels: shoulder pain and healthy controls) and (2 levels: verbal/tactile feedback session versus no intervention). Interaction (IA) effects: time*group*intervention, time*group, time*intervention, and group*intervention were of interest. In absence of an IA effect, main effects for time, group and intervention were explored.
Additionally, an Independent T-test between groups for demographic characteristics and NRS was performed.
Additionally, an Independent T-test between groups for demographic characteristics and NRS was performed.
6
Quantitative Plant Stress Analysis
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Experiments were conducted at least three times with three individual plants (biological replicates) in each experiment. Statistical analysis was performed using IBM SPSS statistics 26 for Windows software. The data were subjected to a one-way analysis of variance (ANOVA). The means of values were compared using Duncan’s least significant range test (p<0.05). Graphs were generated using GraphPad Prism.
7
Emotion-Food Image Association Analysis
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The statistical data analyses were conducted using IBM SPSS Statistics 26 for Windows (IBM, New York, USA), R software version 4.1.1 (The R Foundation for Statistical Computing), and the Python programming language version 3.9 (The Python Software Foundation). Descriptive statistics were used in order to calculate (1) the percentage of the emotion terms that were selected for each food image and (2) the percentage of the food images that were selected for each emotion term. The intraclass correlation coefficient (ICC) estimates and their 95% confident intervals were based on a mean-rating (k = 3), absolute agreement, 2-way mixed-effects model [52 (link),53 (link)]. ICC values less than 0.5 are indicative of poor reliability, values between 0.5 and 0.75 indicate moderate reliability, values between 0.75 and 0.9 indicate good reliability and values greater than 0.9 indicate excellent reliability [52 (link)]. For all of the other analyses, a probability level of p < 0.05 was considered to indicate statistical significance.
8
Prescribing Patterns of Emergency Providers
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Frequencies are presented as N (%) and continuous variables as mean (SD) or median (IQR), according to their distribution. The KolmogorovSmirnov test was used to examine the distribution of continuous variables. The independent-sample median test was used to compare total prescribed MME and also number of pills prescribed between EM vs. non-EM providers. A P value <0.05 was considered statistically significant. IBM SPSS Statistics 26 for windows was used for data analysis.
9
Epidemiological Analysis of Retinoblastoma
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Patients were characterized in terms of demographics (region of birth, sex, age at diagnosis, clinical signs at presentation and familial history of retinoblastoma) and tumor characteristics (eye stage according to ICRB and AJCC, multifocality and laterality). Information regarding time between first diagnosis of lesion suspicious of retinoblastoma in the home country and first observation at our center was also registered.
Epidemiological data, namely annual living births and population under 5 years old, were obtained from the databases of the United Nations Population Fund. These values were used to calculate the estimated expected annual incidence in each country considering 1 per 16,000–18,000 annual incidence of retinoblastoma.
All statistical analysis was performed using IBM SPSS Statistics 26 for Windows.
Epidemiological data, namely annual living births and population under 5 years old, were obtained from the databases of the United Nations Population Fund. These values were used to calculate the estimated expected annual incidence in each country considering 1 per 16,000–18,000 annual incidence of retinoblastoma.
All statistical analysis was performed using IBM SPSS Statistics 26 for Windows.
10
Oropharyngeal Microbiota Modulation by Lactobacilli
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Inhibitory effects in vitro were analyzed using Student's paired t‐test. In the randomized controlled trial, continuous variables were presented as median, minimum, and maximum values. Dichotomous variables were presented as numbers and as a percentage of the total number. For subjects with a normal oropharyngeal microbiota at inclusion, a univariate Poisson regression was used to analyze the association between the patients’ characteristics (predicting variables) and the intervention they were randomized to (dependent variable). Thereafter, a multivariate Poisson regression model using the two strongest predicting variables from the univariate analysis was constructed, in which one additional potential explanatory variable was added to determine whether the model improved or did not improve by including a third variable. A Kaplan–Meyer analysis was performed to test for differences between the placebo and the lactobacilli group regarding “time to first disturbed oropharyngeal swab.” Fisher's exact test was used to assess the relationship between the intervention group and nosocomial infection rate.
Statistical analyses were performed using IBM SPSS Statistics 26 for Windows (IBM Corp., Armonk, NY, USA). Odds ratios (ORs) are presented with a 95% confidence interval. p < 0.05 was considered significant, and all statistical tests were two‐tailed.
Statistical analyses were performed using IBM SPSS Statistics 26 for Windows (IBM Corp., Armonk, NY, USA). Odds ratios (ORs) are presented with a 95% confidence interval. p < 0.05 was considered significant, and all statistical tests were two‐tailed.
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