#metaanalysis — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #metaanalysis, aggregated by home.social.
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DATE: July 30, 2026 at 06:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: New study reveals an unexpected difference between casual and compulsive pornography viewers
A recent meta-analysis of data from over 100,000 individuals reveals a notable relationship between watching pornography and engaging in interactive online sexual behaviors like sexting. The research indicates that recreational viewing of sexually explicit media is more strongly associated with these digital interactions than compulsive watching. The findings were published in the Journal of Sex & Marital Therapy.
Over the past two decades, the Internet has radically transformed how individuals explore and express human sexuality. Researchers generally divide digital sexual behaviors into two broad categories based on social interaction. Solo activities include reading erotic stories or watching adult videos in isolation. In contrast, interpersonal online sexual activities involve direct interaction with at least one other human being.
These interactive behaviors take many forms across digital platforms. They can include exchanging explicit text messages, participating in live webcam sessions, or actively seeking short-term romantic partners through dating applications. While these activities are increasingly common, their psychological motivations and connections to other sexual behaviors remain somewhat ambiguous.
One major question in the field of sexual health revolves around how consuming pornography influences interactive digital behaviors. Previous research on this topic has produced mixed results. Some studies have found a positive association between watching pornography and sending explicit messages. Other studies have uncovered negative associations, while some have failed to find a relationship that was statistically significant.
Xinyue Zhang, a researcher at Southwest University in Chongqing, China, led a team to investigate this discrepancy. Along with colleagues Zhuoren Jin and Lijun Zheng, Zhang set out to aggregate existing data. The researchers wanted to establish a general baseline for how adult media consumption relates to interactive online sexual behaviors in the general population.
The research team grounded their investigation in several established media and psychological theories. One prominent framework operates under the idea that viewing pornography provides consumers with specific scripts about sexual behavior. Exposure to these scripts activates preexisting sexual thoughts or introduces new ones, which individuals then apply in real-world or digital settings.
Another foundational concept involves cognitive priming. This psychological theory suggests that viewing sexual stimuli temporarily alters a person’s mental state. The exposure acts as a trigger, heightening the accessibility of sexual desire and making the individual more likely to seek immediate sexual expression online.
Beyond media influence, the researchers also considered underlying personality traits. Sexual sensation seeking is a known psychological trait describing an individual’s drive for novel and intense sexual experiences. People with high levels of this trait might naturally gravitate toward watching pornography for visual stimulation. At the same time, they might engage in digital sexual interactions for social stimulation, treating both activities as complementary outlets.
To synthesize the existing literature, Zhang and the team conducted a meta-analysis. A meta-analysis is a statistical technique that pools data from multiple independent studies to identify overarching trends that a single study might miss. The researchers systematically searched academic databases for papers containing relevant keywords. They focused strictly on empirical studies involving the general population, excluding clinical research focused on sex offenders.
The final analysis included 40 distinct studies providing a combined sample size of 103,452 participants. In the field of psychology, this represents a large study, providing a highly stable pool of data for estimating behavioral patterns. The researchers extracted the mathematical correlations from each paper and applied specialized models to account for variations between different study designs.
The team utilized a specific method known as a three-level meta-analysis. This statistical approach accounts for different layers of variation, including sampling error within individual groups and broad differences between separate studies. Structuring the analysis this way prevented the researchers from exaggerating the final outcomes.
The researchers also ran tests to check for publication bias. This phenomenon occurs when academic journals preferentially publish studies with dramatic results while ignoring those with null findings. The tests indicated an absence of publication bias, suggesting the pooled data offered a reliable representation of the field.
The pooled data revealed an overall moderate correlation between watching pornography and participating in interpersonal online sexual activity. As the reported frequency of watching sexually explicit media increased, the likelihood of engaging in interactive digital sexual behaviors also rose. This general trend aligned with the researchers’ initial expectations based on media priming and sensation-seeking theories.
However, the strength of this relationship fluctuated depending on the specific type of activity. Digital behaviors directly related to sexual content showed the strongest connection to pornography consumption. These direct behaviors included cybersex and the exchange of explicit images. Behaviors oriented around seeking new partners or maintaining existing romantic relationships showed weaker correlations.
The researchers observed that different forms of sexting did not alter the relationship. Sexting can be characterized as active (sending messages) or passive (being pressured to send or receive messages). The data showed that pornography consumption was equally associated with both forms. The researchers note that exposure to adult media might not only encourage active participation but also foster a higher tolerance for passive or mixed sexting environments.
One of the more nuanced findings emerged when the researchers looked at problem viewing habits. The psychiatric community sometimes categorizes excessive pornography consumption that causes life distress as a form of compulsive behavior. The meta-analysis revealed that non-problematic, recreational viewing was more strongly linked to interactive digital sex than problematic, compulsive viewing.
For recreational users, watching adult content acts as a source of arousal that motivates social sexual interaction. Interactive digital sex requires a degree of interpersonal skill and reciprocal communication. People who exhibit compulsive viewing patterns often use media to regulate negative emotions rather than to pursue social pleasure. As a result, compulsive users might prefer the low-risk solitary act of viewing explicit media over the socially demanding nature of an interactive digital exchange.
The study also examined the role of violence and coercion. Some of the included literature measured coercive online acts, such as the unauthorized distribution of intimate images or digital sexual harassment. The analysis showed a much weaker link between pornography use and violent digital acts compared to consensual, nonviolent activities.
How researchers measured behavior in the original studies also influenced the results. Studies that used comprehensive, multi-question surveys to assess viewing habits found stronger correlations. Questionnaires that asked about multiple viewing formats, such as videos and text, also yielded stronger relationships than surveys measuring only a single format.
The research team notes several caveats in their analysis. Most of the 40 studies included in the review relied on cross-sectional data. This type of research captures information at a single point in time, meaning it is impossible to determine a sequence of events. A correlation is evident, but the data cannot confirm that watching pornography directly causes individuals to engage in interactive digital sex.
Self-reporting introduces another notable limitation, particularly regarding aggressive behavior. People are generally hesitant to admit to participating in coercive or violent digital acts because of intense social and legal repercussions. The researchers suspect that participants in the original studies may have underreported their involvement in these types of activities. This hesitation could artificially suppress the actual correlation between adult media and digital sexual violence.
Future investigations will need to track participants over long periods to establish cause and effect. Longitudinal studies would help researchers understand if early exposure to adult media precipitates later digital interactions or if the two behaviors simply co-occur throughout an individual’s life.
The researchers also emphasize a need for specialized assessment tools. The digital landscape involves unique psychological dynamics, such as anonymity and physical distance. These factors can drastically lower a person’s social inhibitions, leading to behaviors that might not occur in offline settings. Developing standardized questionnaires that account for these digital nuances will help researchers separate harmless recreational habits from pathological compulsions.
The study, “The Association Between Pornography Use and Interpersonal Online Sexual Activity: A Three-Level Meta-Analysis,” was authored by Xinyue Zhang, Zhuoren Jin, and Lijun Zheng.
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Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #PornographyUse #InterpersonalOnlineSex #SextingTrends #DigitalSexualBehavior #SexualHealthResearch #MetaAnalysis #RecreationalViewing #CompulsiveViewing #Cybersex #OnlineSexualBehavior
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DATE: July 30, 2026 at 06:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: New study reveals an unexpected difference between casual and compulsive pornography viewers
A recent meta-analysis of data from over 100,000 individuals reveals a notable relationship between watching pornography and engaging in interactive online sexual behaviors like sexting. The research indicates that recreational viewing of sexually explicit media is more strongly associated with these digital interactions than compulsive watching. The findings were published in the Journal of Sex & Marital Therapy.
Over the past two decades, the Internet has radically transformed how individuals explore and express human sexuality. Researchers generally divide digital sexual behaviors into two broad categories based on social interaction. Solo activities include reading erotic stories or watching adult videos in isolation. In contrast, interpersonal online sexual activities involve direct interaction with at least one other human being.
These interactive behaviors take many forms across digital platforms. They can include exchanging explicit text messages, participating in live webcam sessions, or actively seeking short-term romantic partners through dating applications. While these activities are increasingly common, their psychological motivations and connections to other sexual behaviors remain somewhat ambiguous.
One major question in the field of sexual health revolves around how consuming pornography influences interactive digital behaviors. Previous research on this topic has produced mixed results. Some studies have found a positive association between watching pornography and sending explicit messages. Other studies have uncovered negative associations, while some have failed to find a relationship that was statistically significant.
Xinyue Zhang, a researcher at Southwest University in Chongqing, China, led a team to investigate this discrepancy. Along with colleagues Zhuoren Jin and Lijun Zheng, Zhang set out to aggregate existing data. The researchers wanted to establish a general baseline for how adult media consumption relates to interactive online sexual behaviors in the general population.
The research team grounded their investigation in several established media and psychological theories. One prominent framework operates under the idea that viewing pornography provides consumers with specific scripts about sexual behavior. Exposure to these scripts activates preexisting sexual thoughts or introduces new ones, which individuals then apply in real-world or digital settings.
Another foundational concept involves cognitive priming. This psychological theory suggests that viewing sexual stimuli temporarily alters a person’s mental state. The exposure acts as a trigger, heightening the accessibility of sexual desire and making the individual more likely to seek immediate sexual expression online.
Beyond media influence, the researchers also considered underlying personality traits. Sexual sensation seeking is a known psychological trait describing an individual’s drive for novel and intense sexual experiences. People with high levels of this trait might naturally gravitate toward watching pornography for visual stimulation. At the same time, they might engage in digital sexual interactions for social stimulation, treating both activities as complementary outlets.
To synthesize the existing literature, Zhang and the team conducted a meta-analysis. A meta-analysis is a statistical technique that pools data from multiple independent studies to identify overarching trends that a single study might miss. The researchers systematically searched academic databases for papers containing relevant keywords. They focused strictly on empirical studies involving the general population, excluding clinical research focused on sex offenders.
The final analysis included 40 distinct studies providing a combined sample size of 103,452 participants. In the field of psychology, this represents a large study, providing a highly stable pool of data for estimating behavioral patterns. The researchers extracted the mathematical correlations from each paper and applied specialized models to account for variations between different study designs.
The team utilized a specific method known as a three-level meta-analysis. This statistical approach accounts for different layers of variation, including sampling error within individual groups and broad differences between separate studies. Structuring the analysis this way prevented the researchers from exaggerating the final outcomes.
The researchers also ran tests to check for publication bias. This phenomenon occurs when academic journals preferentially publish studies with dramatic results while ignoring those with null findings. The tests indicated an absence of publication bias, suggesting the pooled data offered a reliable representation of the field.
The pooled data revealed an overall moderate correlation between watching pornography and participating in interpersonal online sexual activity. As the reported frequency of watching sexually explicit media increased, the likelihood of engaging in interactive digital sexual behaviors also rose. This general trend aligned with the researchers’ initial expectations based on media priming and sensation-seeking theories.
However, the strength of this relationship fluctuated depending on the specific type of activity. Digital behaviors directly related to sexual content showed the strongest connection to pornography consumption. These direct behaviors included cybersex and the exchange of explicit images. Behaviors oriented around seeking new partners or maintaining existing romantic relationships showed weaker correlations.
The researchers observed that different forms of sexting did not alter the relationship. Sexting can be characterized as active (sending messages) or passive (being pressured to send or receive messages). The data showed that pornography consumption was equally associated with both forms. The researchers note that exposure to adult media might not only encourage active participation but also foster a higher tolerance for passive or mixed sexting environments.
One of the more nuanced findings emerged when the researchers looked at problem viewing habits. The psychiatric community sometimes categorizes excessive pornography consumption that causes life distress as a form of compulsive behavior. The meta-analysis revealed that non-problematic, recreational viewing was more strongly linked to interactive digital sex than problematic, compulsive viewing.
For recreational users, watching adult content acts as a source of arousal that motivates social sexual interaction. Interactive digital sex requires a degree of interpersonal skill and reciprocal communication. People who exhibit compulsive viewing patterns often use media to regulate negative emotions rather than to pursue social pleasure. As a result, compulsive users might prefer the low-risk solitary act of viewing explicit media over the socially demanding nature of an interactive digital exchange.
The study also examined the role of violence and coercion. Some of the included literature measured coercive online acts, such as the unauthorized distribution of intimate images or digital sexual harassment. The analysis showed a much weaker link between pornography use and violent digital acts compared to consensual, nonviolent activities.
How researchers measured behavior in the original studies also influenced the results. Studies that used comprehensive, multi-question surveys to assess viewing habits found stronger correlations. Questionnaires that asked about multiple viewing formats, such as videos and text, also yielded stronger relationships than surveys measuring only a single format.
The research team notes several caveats in their analysis. Most of the 40 studies included in the review relied on cross-sectional data. This type of research captures information at a single point in time, meaning it is impossible to determine a sequence of events. A correlation is evident, but the data cannot confirm that watching pornography directly causes individuals to engage in interactive digital sex.
Self-reporting introduces another notable limitation, particularly regarding aggressive behavior. People are generally hesitant to admit to participating in coercive or violent digital acts because of intense social and legal repercussions. The researchers suspect that participants in the original studies may have underreported their involvement in these types of activities. This hesitation could artificially suppress the actual correlation between adult media and digital sexual violence.
Future investigations will need to track participants over long periods to establish cause and effect. Longitudinal studies would help researchers understand if early exposure to adult media precipitates later digital interactions or if the two behaviors simply co-occur throughout an individual’s life.
The researchers also emphasize a need for specialized assessment tools. The digital landscape involves unique psychological dynamics, such as anonymity and physical distance. These factors can drastically lower a person’s social inhibitions, leading to behaviors that might not occur in offline settings. Developing standardized questionnaires that account for these digital nuances will help researchers separate harmless recreational habits from pathological compulsions.
The study, “The Association Between Pornography Use and Interpersonal Online Sexual Activity: A Three-Level Meta-Analysis,” was authored by Xinyue Zhang, Zhuoren Jin, and Lijun Zheng.
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #PornographyUse #InterpersonalOnlineSex #SextingTrends #DigitalSexualBehavior #SexualHealthResearch #MetaAnalysis #RecreationalViewing #CompulsiveViewing #Cybersex #OnlineSexualBehavior
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What appeared to reduce #anxiety disorders and symptoms most in a recent #MetaAnalysis?
It had better effects and certainty ratings than #CBT, treatment-as-usual, #aerobics, and several other common interventions.
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What appeared to reduce #anxiety disorders and symptoms most in a recent #MetaAnalysis?
It had better effects and certainty ratings than #CBT, treatment-as-usual, #aerobics, and several other common interventions.
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DATE: July 22, 2026 at 10:56AM
SOURCE: PSYCHIATRIC TIMESDirect article link at end of text block below.
A recent meta-analysis ranked add-on atypical antipsychotics for major depressive disorder, comparing symptom response and dropout risks to guide smarter next-step treatment. https://t.co/3AzkReNJcE
Here are any URLs found in the article text:
Articles can be found by scrolling down the page at Articles can be found at https://www.psychiatrictimes.com/news".
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Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #psychotherapist #MajorDepressiveDisorder #AtypicalAntipsychotics #DepressionTreatment #MetaAnalysis #PsychiatryResearch
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DATE: July 22, 2026 at 10:56AM
SOURCE: PSYCHIATRIC TIMESDirect article link at end of text block below.
A recent meta-analysis ranked add-on atypical antipsychotics for major depressive disorder, comparing symptom response and dropout risks to guide smarter next-step treatment. https://t.co/3AzkReNJcE
Here are any URLs found in the article text:
Articles can be found by scrolling down the page at Articles can be found at https://www.psychiatrictimes.com/news".
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #psychotherapist #MajorDepressiveDisorder #AtypicalAntipsychotics #DepressionTreatment #MetaAnalysis #PsychiatryResearch
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📺 Video recordings of presentations from our recent workshop on "Recent Advances in Meta-Analysis" at @unigoettingen are now available at the University Medical Center's YouTube channel:
👉 https://www.youtube.com/@unimedizin_goettingenIncludes presentations by David Rindskopf, Annika Hoyer, Satoshi Hattori, David Jesse, Wolfgang Viechtbauer (@wviechtb), Renato Panaro (@panaro), Gerta Rücker, Bohua Chen and myself.
See also here for details:
https://medstat.umg.eu/aktuelles/symposium-meta-analysis-2026/ -
📺 Video recordings of presentations from our recent workshop on "Recent Advances in Meta-Analysis" at @unigoettingen are now available at the University Medical Center's YouTube channel:
👉 https://www.youtube.com/@unimedizin_goettingenIncludes presentations by David Rindskopf, Annika Hoyer, Satoshi Hattori, David Jesse, Wolfgang Viechtbauer (@wviechtb), Renato Panaro (@panaro), Gerta Rücker, Bohua Chen and myself.
See also here for details:
https://medstat.umg.eu/aktuelles/symposium-meta-analysis-2026/ -
Recent commentary in Nature Human Behaviour: "The emerging disenchantment with retrospective meta-analysis": https://www.nature.com/articles/s41562-026-02463-y
One thing that bothers me about these types of commentaries is that they are critiquing a method based on instances where it is used poorly. This is in my opinion not a proper critique of a method. I could then write an article about our disenchantment with the linear regression model. Here is my abstract:
"Linear regression is a retrospective and inherently exploratory method with a substantial probability of bias. Researchers typically decide after seeing the data which variables to include, how to code them, whether to transform outcomes, which interaction terms to test, and which observations to exclude as outliers. The method is also vulnerable to omitted-variable bias, model misspecification, multicollinearity, measurement error, and selective reporting of favorable specifications. Because regression analyses are often conducted on observational data collected for other purposes, causal interpretations are particularly problematic. Consequently, linear regression results should generally be regarded as exploratory and hypothesis-generating rather than confirmatory, with properly pre-registered randomized experiments providing a more reliable basis for inference."
Of course one can point out problems with the application of a method in particular instances. But in my opinion this requires much more nuance.
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Recent commentary in Nature Human Behaviour: "The emerging disenchantment with retrospective meta-analysis": https://www.nature.com/articles/s41562-026-02463-y
One thing that bothers me about these types of commentaries is that they are critiquing a method based on instances where it is used poorly. This is in my opinion not a proper critique of a method. I could then write an article about our disenchantment with the linear regression model. Here is my abstract:
"Linear regression is a retrospective and inherently exploratory method with a substantial probability of bias. Researchers typically decide after seeing the data which variables to include, how to code them, whether to transform outcomes, which interaction terms to test, and which observations to exclude as outliers. The method is also vulnerable to omitted-variable bias, model misspecification, multicollinearity, measurement error, and selective reporting of favorable specifications. Because regression analyses are often conducted on observational data collected for other purposes, causal interpretations are particularly problematic. Consequently, linear regression results should generally be regarded as exploratory and hypothesis-generating rather than confirmatory, with properly pre-registered randomized experiments providing a more reliable basis for inference."
Of course one can point out problems with the application of a method in particular instances. But in my opinion this requires much more nuance.
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Meta-analyses may reveal effects not noticeable in individual studies, such as treatment-by-subgroup interactions (e.g. effects in males vs. females). To support Bayesian analysis, prior knowledge on interaction heterogeneity is crucial. @panaro compiled such data, showing heterogeneity is often lower than expected (which makes the derived prior valuable to support formal analyses).
See here for details:👉 https://arxiv.org/abs/2606.23968
(Joint work with @friede1)
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Meta-analyses may reveal effects not noticeable in individual studies, such as treatment-by-subgroup interactions (e.g. effects in males vs. females). To support Bayesian analysis, prior knowledge on interaction heterogeneity is crucial. @panaro compiled such data, showing heterogeneity is often lower than expected (which makes the derived prior valuable to support formal analyses).
See here for details:👉 https://arxiv.org/abs/2606.23968
(Joint work with @friede1)
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The standard random-effects model in meta-analysis assumes that the amount of heterogeneity (i.e., the variance in the true effects) is homoscedastic. This assumption may not be true. I derived and examined a variety of tests for heteroscedastic heterogeneity. Among these, a bootstrapped score test performs quite well. A preprint describing these methods can be found here: https://osf.io/cavhy
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As another alternative to the standard forest plot for visualizing many effect size estimates in a meta-analysis, one can use 'orchard plots' (Nakagawa et al., 2021). Example code to create such figures can be found here: https://www.metafor-project.org/doku.php/plots:forest_plot_orchard_style
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In large meta-analyses, standard forest plot can become excessively large. One solution is to group the estimates together within studies. I just added an example to the metafor website illustrating this possibility:
https://www.metafor-project.org/doku.php/plots:forest_plot_with_grouped_estimates
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🤔 Can you perform a meta-analysis of a single study?
💡 Yes, you can -- this makes perfect sense if you want to derive a "meta-analytic-predictive (MAP) prior" based on a previous study. And it is in fact done implicitly in certain shrinkage applications involving only 2 studies. @friede1 and I had a closer look at this case:
👉 https://doi.org/10.1017/rsm.2026.10081 -
📊 Reliable evidence needs reliable methods.
Co-initiated by RC Trust PI Markus Pauly, the Göttingen symposium “Recent Advances on Statistical Methods for Meta-Analyses” brought together international experts to discuss how researchers can draw valid conclusions when only few studies or small samples are available.
🔗 https://rc-trust.ai/news/news-detail/reliable-evidence-needs-reliable-statistical-methods
#Statistics #MetaAnalysis #RCTrust #TUDortmund -
It's been 84 years... okay, three months, but here's a PhD side quest: a mini meta-analysis.
Analysis & forest plot done in {metafor}, HTML report knitted in RMarkdown, {grateful} for software acknowledgements.
GitHub repo: https://github.com/ale-lazic/vacc_cvrg_meta/
HTML page preview: https://htmlpreview.github.io/?https://github.com/ale-lazic/vacc_cvrg_meta/blob/1d79d6506bc5dca5333fa05cbfb95953817e904b/vacc_cvrg_meta.html
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It's been 84 years... okay, three months, but here's a PhD side quest: a mini meta-analysis.
Analysis & forest plot done in {metafor}, HTML report knitted in RMarkdown, {grateful} for software acknowledgements.
GitHub repo: https://github.com/ale-lazic/vacc_cvrg_meta/
HTML page preview: https://htmlpreview.github.io/?https://github.com/ale-lazic/vacc_cvrg_meta/blob/1d79d6506bc5dca5333fa05cbfb95953817e904b/vacc_cvrg_meta.html
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🎁 Bonus: we provide a template for data extraction — one of the most challenging parts of any meta-analysis.
📋 Template: https://asanchez-tojar.github.io/meta-analysis_badge_of_status_commentary/
💻 Code & data: https://github.com/ASanchez-Tojar/meta-analysis_badge_of_status_commentary
🔗 https://doi.org/10.1002/ece3.73578
#OpenScience #MetaAnalysis #Ecology #Evolution #SystematicReview
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🎁 Bonus: we provide a template for data extraction — one of the most challenging parts of any meta-analysis.
📋 Template: https://asanchez-tojar.github.io/meta-analysis_badge_of_status_commentary/
💻 Code & data: https://github.com/ASanchez-Tojar/meta-analysis_badge_of_status_commentary
🔗 https://doi.org/10.1002/ece3.73578
#OpenScience #MetaAnalysis #Ecology #Evolution #SystematicReview
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A new version (1.6-0) of the metadat package (https://wviechtb.github.io/metadat/) has been released on CRAN (https://cran.r-project.org/package=metadat). The package provides over 100 meta-analytic datasets, which are useful for teaching and testing purposes.
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Analyzing COVID-19 data reveals:
🔹 Fever in 88.5%
🔹 52% discharge rate
🔹 5% fatality rate
🔹 60% affected were male
#MetaAnalysis #COVID19 #Pub2Post https://dev.https://tnyp.me/BUrL4MuV/m -
Analyzing COVID-19 data reveals:
🔹 Fever in 88.5%
🔹 52% discharge rate
🔹 5% fatality rate
🔹 60% affected were male
#MetaAnalysis #COVID19 #Pub2Post https://dev.https://tnyp.me/BUrL4MuV/m -
A new version (5.0-1) of the metafor package has been released on CRAN. It includes some smaller updates, including more ways to visualize prediction intervals / distributions. Further details here: https://www.metafor-project.org/doku.php/news:news #Rstats #MetaAnalysis
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Analysis of COVID-19 Clinical Data:
🩺 Fever - 88.5%, a leading symptom
📊 Lymphocytopenia - 64.5%, prevalent lab finding
🔬 Male patients - 60%
🚑 Discharge - 52%
⚰️ Fatality rate - 5%
#COVID19 #MetaAnalysis #Pub2Post https://tnyp.me/ttsLL7FN/m -
A new #MetaAnalysis finds that vegetarian and vegan diets are linked to lower cancer risk (-13% and -23% for total cancer), adds to the evidence supporting much more plant-based dietary patterns in the general population: doi.org/10.1007/s106... #Review #Vegan #PlantBased #Diets #Cancer #Health
Vegetarian and vegan diets and... -
A new #MetaAnalysis finds that vegetarian and vegan diets are linked to lower cancer risk (-13% and -23% for total cancer), adds to the evidence supporting much more plant-based dietary patterns in the general population: doi.org/10.1007/s106... #Review #Vegan #PlantBased #Diets #Cancer #Health
Vegetarian and vegan diets and... -
📢 Our next #DFG -funded symposium on
"Recent advances in #MetaAnalysis"
will be taking place May 28/29 in Göttingen.
For more details, see here:
➡️ https://medstat.umg.eu/aktuelles/symposium-meta-analysis-2026/
and stay tuned for updates! -
🤔 Meta-analyses considering differences between subgroups within each study ("treatment-by-subgroup interactions") do not necessarily yield matching estimates for effects within subgroups and the difference between them.
💡 @panaro worked out how explicit consideration of information fractions contributed by subgroups in the analysis model allows to fix this counterintuitive behaviour; see here for details:
➡️ https://arxiv.org/abs/2512.18785
(joint work with @friede1). -
Climate change is worse for the others 🌍, people believe. A meta-analysis of 83 studies involving over 70,000 participants across 17 countries reveals that people systematically underestimate their personal climate risk 🌡️.
Read Full Article
#ClimateChange #PersonalRisk #MetaAnalysis #ClimateAwareness #Sustainability https://www.nature.com/articles/s41893-025-01717-3
Reenviado desde Science News
(https://t.me/experienciainterdimensional/9992) -
I did end up making some plots with orchaRd 2.0 last night. Not as pretty as the figures in the package authors' paper (these are rough versions), but I think they still show how informative these plots can be!
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Spent some time today playing around with the R package orchaRd 2.0
It offers a really nice way of visualizing meta-analyses, especially moderator meta-regression models (with both categorical & continuous moderators!)
https://daniel1noble.github.io/orchaRd/
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Thrilled to announce that @shreyadimri and I will be part of #LoveMethods26! 🎉
We'll be running a session on "How to avoid common problems when doing a #systematicReview and #MetaAnalysis", sharing practical tips for conducting reproducible & transparent evidence syntheses
Love Methods Week (January 19–23, 2026) is a FREE online event where researchers come together to learn & share open, reusable methods. There's something for everyone!
👉 Full details & registration: https://excelscior.uc.pt/love-methods-week-2026/
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🤔 Estimation of between-study variability (heterogeneity) is tricky when only few studies are available.
❓ Can we make use of additional information, by considering subgroups within studies?
💡 It turns out we can -- yielding better performance due to fewer zero-estimates and more degrees-of-freedom.
👉 See here: https://arxiv.org/abs/2511.15366
(Joint work with Ao Huang and @friede1 )
