[remlapmot]

• Fixed URL in gwas2020 vignette
• Clarified the steps in the Multivariable MR section of the Perform MR vignette and fixed the object passed to extract_outcome_data() in its example (thanks @hdraisma, Unsure re [Multivariable MR](https://mrcieu.github.io/TwoSampleMR/articles/perform_mr.html#multivariable-mr-1) documentation: ("Re-")extract clumped SNPs from exposures, or from outcome? #340)
• Fixed harmonise_ld_dat(), and hence dat_to_MRInput(get_correlations = TRUE), failing when the LD matrix SNPs were in a different order to the summary data; the LD matrix is now reordered to match (thanks @marwaalarab, Error in harmonise_ld_dat(x, ld) #348)
• Fixed small p-values being shown as 0 in the tables in mr_report() reports; p-values are now shown to 3 significant figures (thanks @sonia-shah, p-value format #42)
• run_mrmix() now removes SNPs with an eaf.exposure that is missing or not strictly between 0 and 1, with a warning, instead of erroring in MRMix::standardize() (MRMix issue #169)
• The mode based estimators (mr_mode(), mr_simple_mode(), mr_weighted_mode(), mr_simple_mode_nome(), and mr_weighted_mode_nome()) now remove SNPs with a beta.exposure of 0, with a warning, instead of erroring with "non-finite 'bw'" in density() (thanks @Julie1130, [BUG]: Error in density.default(BetaIV.in, weights = weights, bw = h) : non-finite 'bw' #570)
• In mv_multiple() and mv_residual() with instrument_specific = FALSE (the default), the nsnp column now reports the number of SNPs used in the analysis, which is all the SNPs, rather than the number passing pval_threshold for each exposure. In mv_residual() this also fixes estimates being set to NA when few SNPs passed pval_threshold for an exposure, even though all SNPs were used (thanks @MaVdb and @mvab, Multivariable MR - P value threshold #78)
• Expanded the documentation of effective_n() to give its formula, explain that it is half the effective sample size used by METAL, and where it is used in the package (thanks @carbocation, effective_n: off by factor of 2? #433)