.. _sphx_glr_auto_examples_02_meta-analyses:

.. _examples-metas:

Performing meta-analyses
------------------------

NiMARE implements a number of coordinate- and image-based meta-analysis algorithms in its :mod:`~nimare.meta` module.
The examples below use :class:`~nimare.nimads.Studyset` as the primary analysis input,
with legacy :class:`~nimare.dataset.Dataset` objects appearing only in preprocessing steps
where older APIs still require them.

For more information about the components that go into coordinate-based meta-analyses in NiMARE, see :doc:`/cbma`,
as well as :doc:`/outputs`.


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    <div class="sphx-glr-thumbcontainer" tooltip="A tour of CBMA algorithms in NiMARE.">

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  .. image:: /auto_examples/02_meta-analyses/images/thumb/sphx_glr_01_plot_cbma_thumb.png
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  :doc:`/auto_examples/02_meta-analyses/01_plot_cbma`

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      <div class="sphx-glr-thumbnail-title">Coordinate-based meta-analysis algorithms</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="A tour of IBMA algorithms in NiMARE.">

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  :doc:`/auto_examples/02_meta-analyses/02_plot_ibma`

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      <div class="sphx-glr-thumbnail-title">Image-based meta-analysis algorithms</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="KernelTransformer classes are tools for converting individual studies&#x27; coordinates into images.">

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  :doc:`/auto_examples/02_meta-analyses/03_plot_kernel_transformers`

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      <div class="sphx-glr-thumbnail-title">KernelTransformers and CBMA</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="An introduction to the Estimator class.">

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  :doc:`/auto_examples/02_meta-analyses/04_plot_estimators`

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      <div class="sphx-glr-thumbnail-title">The Estimator class</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Here we take a look at multiple comparisons correction in meta-analyses.">

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  :doc:`/auto_examples/02_meta-analyses/05_plot_correctors`

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      <div class="sphx-glr-thumbnail-title">The Corrector class</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Run IBMAs and CBMAs on a toy Studyset, then compare the results qualitatively.">

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  :doc:`/auto_examples/02_meta-analyses/06_plot_compare_ibma_and_cbma`

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      <div class="sphx-glr-thumbnail-title">Compare image and coordinate based meta-analyses</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Perform a MACM analysis with Neurosynth data.">

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  .. image:: /auto_examples/02_meta-analyses/images/thumb/sphx_glr_07_macm_thumb.png
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  :doc:`/auto_examples/02_meta-analyses/07_macm`

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      <div class="sphx-glr-thumbnail-title">Meta-analytic coactivation modeling analysis</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Meta-analytic projects often involve a number of common steps comparing two or more samples.">

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  :doc:`/auto_examples/02_meta-analyses/08_plot_cbma_subtraction_conjunction`

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      <div class="sphx-glr-thumbnail-title">Two-sample ALE meta-analysis</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Simulating data before you run your meta-analysis is a great way to test your assumptions and see how the meta-analysis would perform with simplified data">

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  :doc:`/auto_examples/02_meta-analyses/09_plot_simulated_data`

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      <div class="sphx-glr-thumbnail-title">Simulate data for coordinate based meta-analysis</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="NiMARE provides a plethora of tools for performing meta-analyses on neuroimaging data. Sometimes it&#x27;s difficult to know where to start, especially if you&#x27;re new to meta-analysis. This tutorial will walk you through using a CBMA workflow function which puts together the fundamental steps of a CBMA meta-analysis.">

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  .. image:: /auto_examples/02_meta-analyses/images/thumb/sphx_glr_10_plot_cbma_workflow_thumb.png
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  :doc:`/auto_examples/02_meta-analyses/10_plot_cbma_workflow`

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      <div class="sphx-glr-thumbnail-title">Run a coordinate-based meta-analysis (CBMA) workflow</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="A tour of Coordinate-based meta-regression (CBMR) algorithms in NiMARE.">

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  :doc:`/auto_examples/02_meta-analyses/11_plot_cbmr`

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      <div class="sphx-glr-thumbnail-title">Coordinate-based meta-regression algorithms</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="NiMARE provides a plethora of tools for performing meta-analyses on neuroimaging data. Sometimes it&#x27;s difficult to know where to start, especially if you&#x27;re new to meta-analysis. This tutorial will walk you through using a IBMA workflow function which puts together the fundamental steps of a IBMA meta-analysis.">

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  .. image:: /auto_examples/02_meta-analyses/images/thumb/sphx_glr_12_plot_ibma_workflow_thumb.png
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  :doc:`/auto_examples/02_meta-analyses/12_plot_ibma_workflow`

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      <div class="sphx-glr-thumbnail-title">Run an image-based meta-analysis (IBMA) workflow</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="This example shows a conservative way to inspect an ALE result when a coordinate-based meta-analysis does not have enough eligible studies for robust voxelwise inference.">

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  :doc:`/auto_examples/02_meta-analyses/13_plot_qualitative_ale_stat`

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      <div class="sphx-glr-thumbnail-title">Qualitative interpretation of ALE statistic maps</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="When comparing two groups of neuroimaging studies, NiMARE offers three complementary approaches:">

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  :doc:`/auto_examples/02_meta-analyses/14_plot_compare_contrast_strategies`

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      <div class="sphx-glr-thumbnail-title">Comparing ALE-based pairwise contrast strategies</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Standard ALE family-wise error (FWE) correction uses Monte Carlo permutations to build a null distribution of maximum ALE statistics.  For large datasets this can take hours.">

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  :doc:`/auto_examples/02_meta-analyses/15_plot_predictive_ale`

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      <div class="sphx-glr-thumbnail-title">Predictive ALE: fast FWE correction without Monte Carlo</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Once a meta-analysis has been run and a thresholded result is in hand, the natural next question is: how much should we trust it?  NiMARE provides two post-hoc diagnostics that approach this question from complementary angles.">

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  :doc:`/auto_examples/02_meta-analyses/16_plot_jackknife_vs_resampled_stability`

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.. toctree::
   :hidden:

   /auto_examples/02_meta-analyses/01_plot_cbma
   /auto_examples/02_meta-analyses/02_plot_ibma
   /auto_examples/02_meta-analyses/03_plot_kernel_transformers
   /auto_examples/02_meta-analyses/04_plot_estimators
   /auto_examples/02_meta-analyses/05_plot_correctors
   /auto_examples/02_meta-analyses/06_plot_compare_ibma_and_cbma
   /auto_examples/02_meta-analyses/07_macm
   /auto_examples/02_meta-analyses/08_plot_cbma_subtraction_conjunction
   /auto_examples/02_meta-analyses/09_plot_simulated_data
   /auto_examples/02_meta-analyses/10_plot_cbma_workflow
   /auto_examples/02_meta-analyses/11_plot_cbmr
   /auto_examples/02_meta-analyses/12_plot_ibma_workflow
   /auto_examples/02_meta-analyses/13_plot_qualitative_ale_stat
   /auto_examples/02_meta-analyses/14_plot_compare_contrast_strategies
   /auto_examples/02_meta-analyses/15_plot_predictive_ale
   /auto_examples/02_meta-analyses/16_plot_jackknife_vs_resampled_stability