remove old manual

link to readthedocs
minor formatting changes

Author: pollaro

README.md

@@ -1,3 +1,5 @@
-# NLA Toolbox
+# Network Level Analysis (NLA) Toolbox
 
-See included manual for reference information.
+NLA is an extensible MATLAB-based software package for the analysis of behavioral associations with brain connectivity data. 
+
+Documentation is located at [read the docs](https://network-level-analysis-toolbox.readthedocs.io/en/latest)

docs/source/for_developers.rst

@@ -8,6 +8,9 @@ Creating additional edge-level tests
 
 Current tests are located in ``+nla/+edge/+test``. This is where all the current tests are located and also where
 any user-created custom tests will need to be saved. All edge-level test objects must inherit from ``nla.edge.BaseTest``
+
+* **Test object**
+
 ..
     commenting this out because it's broken right now. filed report on github
     .. mat:module:: edge
@@ -25,11 +28,11 @@ any user-created custom tests will need to be saved. All edge-level test objects
   may be used and this step can be skipped. If a new result is needed, a permutation result inheriting ``+nla/+edge/+result/PermBase``
   must also be created
 
-.. mat:module:: edge.result
+  .. mat:module:: edge.result
 
-.. mat:autoclass:: Base
+  .. mat:autoclass:: Base
 
-..     mat:automethod:: output(net_atlas, flags, prob_label)
+    .. mat:automethod:: output(net_atlas, flags, prob_label)
 
 Creating additional network-level tests
 ----------------------------------------------------------

docs/source/index.rst

@@ -21,7 +21,6 @@ Welcome to NetworkLevelAnalysis's documentation!
    network_level_tests
    network_level_results
    for_developers
-   bibliography
 
 
 Indices and tables

docs/source/methodology.rst

@@ -6,8 +6,8 @@ The Network Level Analysis (NLA) Method
 
 First, connectome-wide associations are calculated between ROI-pair connectivity and behavioral data,
 resulting in a set of standardized regression coefficients that specify the brain-behavior association at
-each ROI-pair of the connectome matrix. Next, network level analysis-consisting of transformation of the
-edge-level test statistics and enrichment statistic calculation :cite:p:`AckermanM` - is done to determine which networks are
+each ROI-pair of the connectome matrix. Next, network level analysis, consisting of a transformation of the
+edge-level test statistics and enrichment statistic calculation :cite:p:`AckermanM`, is done to determine which networks are
 strongly associated with the behavior of interest.
 
 Both *p*-value and test-statistic binarization are offered in the current NLA pipeline :cite:p:`EggebrechtA,WheelockM:2018`. Prior research has
@@ -22,7 +22,7 @@ applications :cite:p:`ChenJ,NewtonM,YaariG,EfronB`.
 Permutation testing
 """"""""""""""""""""""""""""""""""""""""""""""""""
 
-Permutation testing can be used to provide approximate control of false positives and allow use of different statistics.
+Permutation testing can be used to provide approximate control of false positive results and allow wide variety of test statistics.
 This is done under the assumption that the data are exchangeable under the null hypothesis - the joint distribution of the
 error terms don't change with the permutation.