Nope, the null effect is either 0 (for continuous outcome) or 1 for dichotomous outcomes (representing an odds ratio or risk ratio).
I don't understand why 0.62 would stand for, except if 0.62 is considered as a minimal clinically relevant effect for a continuous outcome (ex: if the difference is
As Sebastien told you the null effect is either O or 1
In the figure the line does not represent the line of no effect, it represent the value of the overall as you can see in the diamond at the final, as the forest plot is a forest plot of subgroups they give you a suboverall per division indicated with the blue diamonds, and at the final an overall effect
In this case the forest plot doe snot have a line of no effect, this could be becasue the meta analysis could be talking about proportions, but there is need to read the captation of the figure to be more precise
In a forest plot, the "line of no effect" typically represents the null hypothesis, indicating no difference or no effect between groups or interventions being compared. The value of this line is often chosen as 0 or 1 depending on the context of the data being presented.
However, theoretically, the line of no effect could be set to any value depending on the research question, the scale of measurement, and the context of the data. For example:
Risk Ratios and Odds Ratios: In epidemiological studies, where risk ratios and odds ratios are commonly used, the line of no effect is often set at 1. A value of 1 suggests no difference in risk or odds between the groups being compared.
Mean Differences: In studies comparing means between groups, the line of no effect could be set at 0. This indicates no difference in means between the groups.
Other Scales: Depending on the scale of measurement, the line of no effect might be set at different values. For instance, if the outcome is on a different scale (e.g., a score on a psychological scale), the line of no effect might correspond to the mean or median score in the reference group.
So while 0 and 1 are common choices for the line of no effect, it can theoretically be set to any value relevant to the interpretation of the data and the research question being addressed. However, it's essential to clearly specify the chosen value and rationale for it in the context of the study when presenting a forest plot.
The line in the figure is the line for total effect size. This is an option in SPSS to ease the compare the effect size for an individual study with the total effect size.
In a forest plot, the "line of no effect" typically represents a null effect or a reference point against which the effect sizes of different studies are compared. This line is often drawn at a value of 0 on the x-axis, indicating no effect or no difference between groups or conditions being compared.
In some cases, depending on the context of the data being presented in the forest plot, the line of no effect may be positioned at a value other than 0 or 1. This could occur when:
Different Baseline Values: If the outcome being measured has a baseline value that is not zero, the line of no effect may be positioned at the baseline value rather than zero. For example, if the baseline value for a particular outcome is 50, the line of no effect might be drawn at 50 instead of 0.
Alternative Reference Point: In certain analyses or comparisons, researchers may choose a different reference point as the line of no effect based on theoretical or practical considerations. For instance, if the effect sizes are ratios or percentages, the line of no effect might be set at 1 instead of 0.
Non-Numerical Variables: In some cases, forest plots may display categorical variables or non-numeric data where the concept of a "line of no effect" may not be applicable in the same way as with continuous numerical data.
Overall, while the default position for the line of no effect in a forest plot is typically at 0 on the x-axis, it can be set to other values depending on the specific context and nature of the data being presented.