[R] Partial correlation test

Jeff Newmiller jdnewmil at dcn.davis.CA.us
Mon Aug 26 06:50:32 CEST 2013


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Sent from my phone. Please excuse my brevity.

Moshiur Rahman <mrahmankufmrt at gmail.com> wrote:
>Dear all,
>
>I'm writing my manuscript to publish after analysis my final data with
>ANOVA, ANCOVA, MANCOVA. In a section of my result, I did correlation of
>my
>data (2 categirical factors with 2 levels: Quantity & Quality; 2
>dependent
>var: Irid.area & Casa.PC1, and 1 co-var: SL). But as some traits (here
>Irid.area) are significantly influenced by the covariate (standard
>length,
>SL), I need to use the partial correlation. I know how to calculate it
>with
>JMP, but as I used R to analyse all of my data (first time in my life)
>for
>this manuscript, can anyone help me to find a solution for this
>problem? I
>got some libraries to calculate it (e.g. ppcor, ggm, etc.), but none of
>them fit to my required analysis (fitting covariate and subset group)
>in
>the model.
>
>Any help will be very much appreciated.
>
>  > ### Datafrmame> data1 <- read.csv(file.choose(),header=TRUE)
>#Partial correlation.csv> data1    Quantity Quality    SL Irid.area
> Casa.PC1
>1       High     Low 16.38     10.31  1.711739555
>2       High    High 15.95     16.52  0.013383537
>3       High    High 15.69     12.74  2.228490878
>4       High     Low 14.76      9.80  1.554975833
>5       High     Low 14.63     12.95  1.823767970
>6       High    High 14.32     14.21  3.152059841
>7       High    High 14.95     12.57  2.069265040
>8       High     Low 15.37     13.55  1.886027422
>9       High     Low 14.73     14.18  1.127440602
>10      High    High 16.08     15.98  1.435563307
>11      High    High 15.78     16.76  2.433261686
>12      High     Low 15.22     12.12  0.927454986
>13      High     Low 14.22     10.91  2.328899576
>14      High    High 14.47     11.03  1.522923487
>15      High     Low 13.98     10.03  2.342535074
>16      High     Low 14.99     11.44  0.749529924
>17      High    High 16.51     20.16  2.993905677
>18      High    High 14.83     16.82  2.227315597
>19      High     Low 15.17     19.21  1.685063793
>20      High     Low 16.29     20.31  1.551704440
>21      High    High 16.23     15.03  1.982319336
>22      High    High 14.18     14.80  1.839910851
>23      High     Low 16.11     12.92  1.443240647
>24      High     Low 13.95      7.60  2.034192171
>25      High    High 17.54     17.80  2.188306237
>26      High     Low 16.24     19.29  1.531264746
>27      High    High 14.79     12.98  1.465644134
>28      High     Low 15.87     14.85  1.372494892
>29      High    High 16.09     13.71  1.462037152
>30      High     Low 14.34     13.53  1.365588960
>31      High    High 14.93     12.91  0.729212386
>32      High    High 15.89     16.98  0.136175317
>33      High     Low 16.11     11.93  1.442761666
>34      High     Low 15.25     15.49  0.834442777
>35      High    High 15.84     17.65  1.471713978
>36      High    High 15.61     18.00  1.949457500
>37      High     Low 15.42     13.87  0.200098471
>38      High     Low 14.91     11.23  0.981988071
>39      High    High 15.69      5.74 -0.445941360
>40      High    High 15.13      9.07  1.387947896
>41      High     Low 15.04     15.87  1.480980400
>42      High     Low 17.08     17.24  2.620029423
>43      High    High 15.85     12.47  0.027278890
>44      High    High 15.35     10.44  2.597373230
>45      High     Low 15.62     12.11  0.030653396
>46      High    High 17.96     17.50  1.544922124
>47      High     Low 17.25     17.87  1.705053951
>48      High     Low 15.56     19.72  1.688867665
>49      High    High 16.27     13.15  0.111371757
>50      High     Low 16.68     15.43  1.538012366
>51      High    High 15.78     15.07  0.744555741
>52       Low    High 14.72     13.34 -0.682505420
>53       Low     Low 14.93     14.07 -1.641494605
>54       Low    High 13.94     13.22 -1.172268647
>55       Low    High 14.01     18.65 -0.996656064
>56       Low     Low 14.33     17.16 -1.789728167
>57       Low     Low 14.57     12.43 -0.827526343
>58       Low    High 14.01     15.29 -1.350691602
>59       Low     Low 14.22     16.98 -1.688278221
>60       Low    High 13.45     14.40 -1.182117327
>61       Low    High 13.44     16.57 -1.358976542
>62       Low     Low 14.76     15.58  0.334534454
>63       Low     Low 14.85     17.65  0.251766383
>64       Low    High 13.42     10.99 -0.526634460
>65       Low    High 14.07     16.88 -1.112579922
>66       Low     Low 14.15     16.41 -0.971918177
>67       Low     Low 14.78     11.95 -1.179074800
>68       Low    High 14.84     17.62 -0.777057705
>69       Low    High 15.16     14.09 -1.224388816
>70       Low     Low 14.60     15.03 -0.775478528
>71       Low    High 13.74     10.01 -0.917153842
>72       Low    High 13.54     12.34 -0.822895877
>73       Low     Low 14.04     11.86  0.002789116
>74       Low    High 15.73     18.50 -1.209469875
>75       Low     Low 15.14     16.85 -0.479090055
>76       Low     Low 14.86     17.32 -1.897204235
>77       Low    High 14.43     11.20  0.469569392
>78       Low     Low 14.01     15.55 -1.025059269
>79       Low    High 14.20     11.67 -0.770451072
>80       Low    High 16.16     17.34 -0.274527631
>81       Low     Low 14.63     13.52 -1.070187945
>82       Low     Low 15.83     14.85 -1.627211162
>83       Low    High 14.70     14.81 -1.694118608
>84       Low    High 13.91     14.48 -1.635459183
>85       Low     Low 13.95     16.05 -1.449612666
>86       Low     Low 14.03     12.58 -1.685968841
>87       Low    High 14.82     13.57 -0.097426417
>88       Low    High 14.32     12.16 -1.403512009
>89       Low     Low 14.33      7.66 -1.336654713
>90       Low     Low 15.01     10.15 -1.257019268
>91       Low    High 14.01      9.79 -0.715404495
>92       Low     Low 14.25     17.38 -1.296954022
>93       Low    High 14.55     16.11 -0.616895943
>94       Low    High 13.98     11.49 -0.654017365
>95       Low     Low 15.59      8.43 -1.708330027
>96       Low     Low 15.02     16.88 -1.352913634
>97       Low    High 13.99      9.64 -0.499793618
>98       Low     Low 13.98     12.25 -1.265336955
>99       Low    High 13.94     13.79 -0.263925513
>100      Low     Low 15.03     20.39 -0.720121308
>101      Low     Low 13.93     14.63 -0.908570400> ### COrrelation
>test according to group> library("MASS")> with(data1, cor.test(~
>Irid.area + Casa.PC1, subset=(Quantity=="High")))# gives cor, df+2,
>p-values
>	Pearson's product-moment correlation
>
>data:  Irid.area and Casa.PC1
>t = 1.5795, df = 49, p-value = 0.1206
>alternative hypothesis: true correlation is not equal to 0
>95 percent confidence interval:
> -0.05905155  0.46734855
>sample estimates:
>      cor
>0.2201142
>> with(data1, cor.test(~ Irid.area + Casa.PC1,
>subset=(Quantity=="Low")))# gives cor, df+2, p-values
>	Pearson's product-moment correlation
>
>data:  Irid.area and Casa.PC1
>t = -0.4275, df = 48, p-value = 0.6709
>alternative hypothesis: true correlation is not equal to 0
>95 percent confidence interval:
> -0.3342116  0.2205349
>sample estimates:
>        cor
>-0.06159377
>> #### Effect size from two-way ANOVA ####> anova<- aov(Irid.area ~
>Quantity*Quality+SL, data=data1)> summary(anova)                 Df Sum
>Sq Mean Sq F value   Pr(>F)
>Quantity          1    0.0    0.04   0.004    0.947
>Quality           1    0.3    0.26   0.032    0.859
>SL                1  149.5  149.49  18.027 5.03e-05 ***
>Quantity:Quality  1    0.2    0.18   0.022    0.883
>Residuals        96  796.1    8.29
>---
>Signif. codes:  0 �***� 0.001 �**� 0.01 �*� 0.05 �.� 0.1 � � 1 >
>etaSquared( anova ) # effect size                       eta.sq
>eta.sq.part
>Quantity         5.682119e-02 0.0632542041
>Quality          6.577118e-05 0.0000781554
>SL               1.510031e-01 0.1521470868
>Quantity:Quality 1.922552e-04 0.0002284211> ### partial correlation
>(pcor) tests:> library(ggm)Loading required package: graphError in
>loadNamespace(i[[1L]], c(lib.loc, .libPaths())) :
>  there is no package called �BiocGenerics�In addition: Warning
>messages:1: package �ggm� was built under R version 2.15.3 2: package
>�graph� was built under R version 3.0.1 Error: package �graph� could
>not be loaded> data2<- data1[, c("Irid.area", "Casa.PC1", "SL"),
>Quantity == "High"]> pcor(c("Irid.area", "Casa.PC1",
>"SL"),var(data2))Error in match.arg(method) : 'arg' must be NULL or a
>character vector> pc<-pcor(data2)> pc$estimate
>           Irid.area   Casa.PC1        SL
>Irid.area  1.0000000 -0.1313475 0.3387663
>Casa.PC1  -0.1313475  1.0000000 0.5061438
>SL         0.3387663  0.5061438 1.0000000
>
>$p.value
>             Irid.area     Casa.PC1           SL
>Irid.area 0.0000000000 1.896426e-01 3.647247e-04
>Casa.PC1  0.1896425857 0.000000e+00 6.258573e-09
>SL        0.0003647247 6.258573e-09 0.000000e+00
>
>$statistic
>          Irid.area  Casa.PC1       SL
>Irid.area  0.000000 -1.311637 3.564375
>Casa.PC1  -1.311637  0.000000 5.809698
>SL         3.564375  5.809698 0.000000
>
>$n
>[1] 101
>
>$gp
>[1] 1
>
>$method
>[1] "pearson"
>
>
>
>
>Cheers,



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