Summary of observed scenarios / variants of changing Impact Factor (IF).

<p>(A) IF increases (left bars) and decreases (right bars) for each annual step 2010–11 to 2013–14. IF increases are further classified as valid or invalid according to the classification in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154199#pone.0154199.g003" target="_blank">Fig 3</a>. (B) The observed IF changes (n = 179) over the four annual steps are classified according to the scenarios explained in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154199#pone.0154199.g003" target="_blank">Fig 3</a> and illustrated for their relative frequency. Invalid IF changes (a3 and a4) are highlighted by red boxes. (C) Overall distribution of journals regarding to the validity of their IF changes. (D) Longitudinal development of each journal in the sample cohort. IF increases, IF decreases and invalid IF increases are indicated by green / red color or red boxes, respectively.</p

Observed maximum changes of citations, articles and Impact Factors.

<p>Observed maximum changes of citations, articles and Impact Factors.</p

Range of Impact Factor changes (ΔIF) for 2014 versus 2013.

<p>(A) ΔIFs for all 10,754 journals with a listed IF for 2013 and 2014. (B) ΔIFs for the journals (n = 49) in the selected study cohort (threshold ΔIF ≥ 3.0). In- and decreasing IFs are highlighted green or red, respectively. The 49 journals in the sample cohort are subsequently identified by a unique identifier (#1 - #49).</p

Annual changes of the Impact Factor (IF) and its variables (citation versus article numbers).

<p>For the annual changes (A-D) of the IF, the relation of relative changes of the number of citations versus articles is shown in each diagram by blue and grey columns, respectively. Each column shows the relative change (%) in relation the numbers of citations or articles in the preceding year. Below each diagram, the ΔIF for each annual step is classified ‘invalid’ as defined in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154199#pone.0154199.g003" target="_blank">Fig 3</a> and indicated by a red box behind the journal ID. The 49 journals in the sample cohort are identified by a unique identifier (#1 - #49).</p

Sample selection.

<p>From all journals listed with an Impact Factor (IF) in the Science Citation Index (SCI) or Social Sciences Citation Index (SSCI), those were selected for further analysis which showed a change of the IF (ΔIF) equal or greater than a threshold of 3.0.</p

Possible scenarios explaining a changing Impact Factor (IF).

<p>(A) Based on theoretical considerations regarding the potential influence of the variables (citations and article numbers) on the final calculation (i.e. the IF quotient), 13 scenarios are possible which either cause an increased (a1-a5), constant (b1-b3) or decreased IF (c1-c3). In those scenarios where necessary, the size of the arrows indicate the relative importance of the changes (articles (Δ(art)) versus citations (Δ(cit))). (B) The validity of these IF changes as a parameter of (changing) journal quality is categorized and referred to as either ‘valid’ (highlighted green) or ‘invalid’ (highlighted red). See text for further explanation.</p

Characteristics of the 24 SNPs in SAPHIR, KORA F3 and CoLaus, including genotype quality (call rate or imputation quality RSQR).

*<p>Minor and Major alleles based on the plus-strand.</p>**<p>Number of homozygotes for the major allele/heterozygotes/homozygotes for the rare allele; For KORA F3 and CoLaus, where imputed genotype scores have been used, this are the numbers of the “best guess” genotypes (KORA F3) and rounded sum of genotype scores.</p>***<p>Based on exact test of Hardy-Weinberg Equilibrium (HWE).</p

Linear model results on the 24 selected SNPs in the SAPHIR, KORA F3 and CoLaus study using an additive genetic model, adjusted for age, sex and BMI, as well as the combined fixed effects meta-analysis results.

<p>Effect estimates and standard errors (for the combined as well as sex-specific analyses) are based on the original adiponectin scale, whereas p-values are taken from the linear regression on log(adiponectin).</p

Schematic structure of <i>SREBF1</i> gene.

<p>Exons are numbered indicating the alternatively spliced -a and -c variants. Genomic location of the analyzed single nucleotide polymorphisms are marked. The single nucleotide polymorphisms highlighted in yellow showed a strongly associated with adiponectin levels in our study. The single nucleotide polymorphism highlighted in grey showed a significant association in a previous study <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052497#pone.0052497-Felder1" target="_blank">[26]</a> and was only borderline significantly associated in the present study (p = 0.004).</p

Linkage disequilibrium structure across the <i>SREBF1</i> single nucleotide polymorphisms.

<p>The pair wise linkage disequilibrium (R² and D’) is given for each pair of single nucleotide polymorphisms. Color-coding is based on R². The diagonal line indicates the physical position of the single nucleotide polymorphisms relative to each other.</p